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AITopics/Bioinformatics
Bioinformatics at Stanford University. By Russ B. Altman. "The following offers a summary of information about bioinformatics at Stanford. It is meant as advisory information for people interested in bioinformatics, written from my own perspective." Biomedical Security Institute - a collaboration between Carnegie Mellon University and the University of Pittsburgh.
AITopics/BridgeDo not pass Go. Computers can beat the world's best chess players but have yet to master other classic games like Go. By David Levy. The Guardian (October 24, 2002). "Ever since Garry Kasparov's sensational 1997 loss to the IBM chess monster Deep Blue, the chess world has thirsted for revenge. But the first opportunity ended in failure in Bahrain on Saturday, when Kasparov's former pupil and successor as World Champion, Vladimir Kramnik, could only draw an 8-game match against one of the world's leading chess engines, Fritz. But this was just the latest in a long series of human versus computer encounters that illustrate the inexorable march of artificial intelligence (AI). It's a story that began at a Dartmouth University conference in 1956, when several of the founding fathers of AI defined the goals of that infant science. One of them was to create a computer program that could defeat the world chess champion. Success would, those scientists believed, reach to the very core of human intellectual endeavour. By the early 1990s, due in no small part to the successes achieved in computer chess, the interest of the AI community had spread to many other games of skill, including backgammon, bridge, Go and Scrabble. Where exactly are we now in this fascinating struggle? ... Two games proving even tougher to crack than chess are bridge and Go." Internet Bridge Archive. Maintained by Marcus Buchhorn, Australian National University. Scroll down the page to get Computers and Bridge link. Scroll further for an interesting newsgroup discussion thread on what needs to be considered in writing bridge playing programs. AITopics/BusinessImagination at Work - Robots. Supercomputers. AI. Five CIO 100 honorees are boosting revenue, cutting costs and maybe saving the planet with these and other cool technologies. Editorial by Meridith Levinson. CIO (August 15, 2006). "If necessity is the mother of invention, then capitalism is surely the mother of innovation. Five of this year's CIO 100 honorees were driven to develop unique applications of undeniably cool technologies by the almighty dollar (the need to make it and to save it). ... To prevent its energy costs from skyrocketing, public utility JEA implemented an intelligent system that determines the perfect mix of oil and natural gas to produce electricity while minimizing nitrous oxide emissions. ... The Ohio State University Medical Center freed up maintenance staff and increased customer satisfaction by deploying robots to handle tasks such as removing trash and transporting meals." This article is part of their special Business Intelligence report. Eureka! Knowledge Discovery. By Neena Buck. Software Magazine. December 2000/January 2001 cover story. "Knowledge discovery and data mining (KDD) is evolving from an esoteric art and a point solution, to a mainstream technology embedded in a variety of solutions, to help businesses turn information into insight." Intelligent Software. By Helen Atkinson. DC Velocity Magazine (July 2003). "Sure you have plenty of brainpower. But when it comes to complex logistics or warehousing decisions, an intelligent software 'agent' may be able to make the call better, faster or more cost effectively than you can." Artificial Intelligence ...Within. Artificial Intelligence methods continue to provide upfront benefits in industrial and consumer arenas, although they're increasingly found working quietly in the background. By Frank J. Bartos. Control Engineering (September 1, 2003). "Perhaps we don't hear much about artificial intelligence (AI) methods used within today's technologies because it's slightly unnerving when computers emulate human thinking. Yet we, and computers themselves, continue to improve the way AI works quietly in the background to optimize, reduce process costs, and improve timing and product quality. For some tough, nonlinear applications, AI may be the only solution. ... Actually, AI consists of various technologies—expert systems, fuzzy logic, artificial neural networks, and genetic algorithms, among others." This article not only explains the technology, but also provides examples of many real world applications. Watch that eek-mail. By Chen Bin. The Straits Times (January 14, 2003). "I refer to the case of a manager being sued for defamation by a rival firm ('Manager sued over e-mail to his staff'; ST, Jan 8) based on the contents of an internal e-mail. This case has once again highlighted the potential risks associated with e-mail use in today's business environment. ... The good news is that there are affordable technology solutions in the market to automate the management of e-mail use. E-mail filtering technology developed with artificial intelligence can scan all the e-mail and look for potential risks before they are allowed to go through. Organisations can use e-mail filtering tools to define their own control rules which will then be enforced automatically." Harnessing Artificial Intelligence in Heavy Industry. CANMET Energy Technology Centre - Ottawa. "Heavy industry is enlisting artificial intelligence - an advanced computer science that seeks to approximate some of the capacities of the human brain - to automate complex processes and extend the skills of human operators. Well-considered application of the technology can boost productivity, quality and energy efficiency, according to a report by the Emerging Technologies Program. ... About 70 percent of all AI installations in heavy industry are expert systems; the remainder are neural networks and fuzzy logic systems. ... Some 40 percent of AI applications in heavy industry involve process control. ... Users report a wide range of benefits from the use of AI, including improved decision making, more responsive control, more efficient material flow, increased labour efficiency, greater consistency in product quality and reduced maintenance costs." "As I was preparing to write this article, I searched the CIO.com website to see if my topic had a name. Lo and behold, not only did it have a name, but Tom Davenport wrote an article about it. [Decision Evolution; October 1, 2004.] 'It' is what he called, 'automated decision systems.' In his article, Mr. Davenport observed that we have moved beyond decision support systems to something that is more powerful and more useful than has been realized in the past. The promise of artificial intelligence, and all of its successors, is beginning to be realized in real world applications. I found myself agreeing with his main points while experiencing keen a sense of déjà vu. Over the years, I've read similar comments about earlier generations of the next big thing in IT that did not live up to the hype, including artificial intelligence (AI), as Davenport notes. In his concluding paragraph, he states: 'This brave new world has been along time coming, but it is clearly upon us now. Businesses need to incorporate automated decision making into their strategies and processes or they won't be successful very long…' Is he accurately predicting the future, or will this be another case of over-promise, under-deliver? As CIO, you will need to make that call. Make the right decision and you're a hero. Guess wrong and you're not. For what it's worth, after much soul searching, I agree with Davenport. This time it's for real. His call for action is prudent, and CIOs need to act now." 'Intelligent' grinding may save $1 billion. United Press International / available from The Washington Times (May 6, 2004). "Researchers at Indiana's Purdue University are working to develop an 'intelligent' grinding system that could save U.S. companies $1 billion annually. The savings would come in manufacturing costs by improving precision-grinding processes for parts production. ... [Yung] Shin said his team of researchers hope to develop a system that enables 'relatively inexperienced employees to operate grinding machinery with the same precision as these rare, highly experienced workers.' The 'intelligent optimization and control grinding processes' use artificial-intelligence software, which mimics how people think, in order to learn and adapt to changing conditions."
Integrated Reasoning Projects from the National Research Council of Canada. Among the many projects you'll discover here is The Paper Maker's Advisor (PMA): "a monitoring and diagnostic system for use in paper mills." OSHA eTools: "eTools are 'stand-alone,' interactive, Web-based training tools on occupational safety and health topics. They are highly illustrated and utilize graphical menus. Some also use expert system modules, which enable the user to answer questions, and receive reliable advice on how OSHA regulations apply to their work site. Expert Advisors are based solely on expert systems." BU grad finds pattern for success - Vestal man's embroidery technology impacts textile industry. By My-Ly Nguyen. Press & Sun-Bulletin (March 2, 2003). "Five computer work stations, a commercial embroidery machine and a lot of brain power are nearly all David Goldman needs to run his growing business, Soft Sight Inc. The software company he founded in August 1998, after earning his doctorate in computer science at Binghamton University, may revolutionize the textile industry with its flagship product: one of the first embroidery design automation systems to hit the global market. ... Goldman's product digitally automates the embroidery design process using sophisticated artificial intelligence software that can mimic the thought and decision process of a human counterpart. A scanned image is used to generate the stitch placement needed to optimally sew the image on a commercial embroidery machine. Human error is dramatically reduced and the costs of producing embroidered apparel can decrease significantly, Goldman said. 'We haven't seen a program of this sophistication before,' said Larry Lawley, president of Data-Stitch Inc., an embroidery equipment and software company based in the Dallas/Fort Worth, Texas area. 'The technology's impact on the industry has been phenomenal.' ... Goldman and his team are continually working to enhance the automation technology with help from the National Science Foundation and Binghamton University." Agent-Based Systems for Intelligent Manufacturing: A State-of-the-Art Survey. By Weiming Shen and Douglas H. Norrie. (1999). Knowledge and Information Systems 1(2); 129-156. "Abstract. Agent technology has been considered as an important approach for developing distributed intelligent manufacturing systems. A number of researchers have attempted to apply agent technology to manufacturing enterprise integration, supply chain management, manufacturing planning, scheduling and control, materials handling, and holonic manufacturing systems. This paper gives a brief survey of some related projects in this area, and discusses some key issues in developing agent-based manufacturing systems such as agent technology for enterprise integration and supply chain management, agent encapsulation, system architectures, dynamic system reconfiguration, learning, design and manufacturability assessments, distributed dynamic scheduling, integration of planning and scheduling, concurrent scheduling and execution, factory control structures, potential tools and standards for developing agent-based manufacturing systems. An extensive annotated bibliography is provided.' Manager's Guide to Neural Networks. From Z Solutions. "From the standpoint of an individual manager's team, the challenge is increasingly one of understanding and organizing large amounts of information to improve knowledge of the organization's business and markets." AITopics/CaseBasedReasoningA Discourse on Law and Artificial Intelligence. By Michael Aikenhead (1996). 5 Law Technology Journal 1. "[T]he dichotomy between rule based systems and cased based reasoning systems in AI and law research reflects an underlying jurisprudential debate that has raged for the last century. ... Instead of implying that legal reasoning is primarily a process of deduction or a process of analogising the theory of law as discourse requires a richer view of the process of legal reasoning."
Nagel, Rebecca Thompson. June/July 1998. HAL, Esq. - Will computers someday replace attorneys in the delivery of legal services? We profile one woman whose work with artificial intelligence could forecast the future of the profession. Law Office Computing (subscription req'd.). "A computer that can think like an attorney? Artificial intelligence in a real-life application? Science fiction, right? Well, a system like the one described above is not yet available...commercially. But it does exist in the laboratory of University of Massachusetts, Amherst professor Dr. Edwina Rissland. ... The key to these programs is case-based reasoning (CBR) -- a subsection of AI that uses examples and analogy, as opposed to rules or logic, to solve problems." AITopics/CheckersKonane -- Hawaiian Checkers. From Peter Ingebretson. "About the Game: Konane is an old Hawaiian game, similar to many varieties of checkers. Strategy is reasonably simple, but the game is difficult to win against a talented opponent. The AI playing this game uses a simple minimax algorithm, with alpha-beta pruning to reduce the size of the search tree. As such, it is quite challenging when searching moves deeper than five or six turns in advance." AITopics/Chess
Deep Blue victory still a milestone 10 years later. By Julie Moran Alterio. The Journal News (May 6, 2007). "$137.50. That's how much it costs today to buy the home version of the Deep Fritz software that beat world chess champion Vladimir Kramnik in a match last year. What a difference a decade makes. This week marks the 10th anniversary of the first time a computer bested a reigning world chess champ. That feat cost Armonk-based IBM Corp. about $5 million. The face-off between IBM's Deep Blue and Garry Kasparov in New York City culminated in a victory for machine over man in the final joust of the six-game match May 11, 1997. ... What might be surprising to contemplate today is how much Kasparov was favored to win at the time of the match. ... The first computer chess programs date to the 1950s, including one written for an IBM 704 mainframe that took 8 minutes to make a move and could be defeated by a beginner. ... When he was interviewed on National Public Radio, a caller asked what the big deal was, didn't they just program the moves into the computer, [Joel] Benjamin recalled. 'A lot of people didn't realize just how historic it was because even then computers were credited with being able to do anything,' he said." Chess Is Too Easy. By Selmer Bringsjord. Technology Review. March/April 1998. "The victory last spring by IBM's Deep Blue computer over the world's greatest human chess player, Gary Kasparov, obliterated Dreyfus's prediction. But does it also argue for Strong rather than Weak AI ?" The Game of Chess. By Herbert A. Simon and Jonathan Schaeffer. Handbook of Game Theory with Economic Applications, vol. 1, Robert J. Aumann and Sergiu Hart (editors), Elsevier Science Publishers, Netherlands, pp. 1-17, 1992. (Also available as CMU technical report AIP-105.) Available in several formats from CiteSeer.
Link to Review of book: , bgb , 10/17/08 and its collection of "Ask the Expert" questions (and answers) about computer chess. Standage, Tom. The Turk: The Life and Times of the Famous Eighteenth-Century Chess-Playing Machine. Walker & Company, New York, 2002. "Part historical detective story, part biography, The Turk relates the saga of the machine's remarkable and checkered career against the backdrop of the industrial revolution, as mechanical technology opened up dramatic new possibilities and the relationship between people and machines was being redefined. Today, in the midst of the computer age, it has assumed a new significance, as scientists and philosophers continue to debate the possibility of machine intelligence. To modern eyes, the Turk now seems to have been a surprisingly farsighted invention, and its saga is a colorful and important part of the history of technology." From the "About the Book" page in the book's web site where you'll also find an interview with the author, Chater One of the book, and much more. AITopics/CommonSenseNewcomer's Guide to Commonsense Computing. From Commonsense Computing @ Media [the MIT Media Lab]. "Why give computers common sense? What does it even mean to give computers common sense? Here are several articles explaining why this problem is both challenging and important to solve if we want to take our computing technology to the next level." FIXED: , bgb , 10/17/08
Guess who's smarter. As sophisticated as computing has become, machines still lack the common sense of a 3-year-old. But MIT artificial intelligence researchers are tackling ways to start building that basic breadth of knowledge into programs and applications. By D.C. Denison. The Boston Globe (May 26, 2003; page D1). "But now there are signs that 'common sense' artificial intelligence research may be making a comeback, sparked by projects like [Push] Singh's Open Mind database. For the first time, after decades of theoretical research, researchers and programmers have begun using a freely distributed, natural language common sense database to start the process of building common sense into products, programs, and applications. In fact, as Singh sits in his cramped office in the Media Lab, he's able to point in the direction of a number of MIT researchers using his database for applications that may soon bring common sense AI to consumers. A few doors down to the right, Barbara Barry, a graduate student in the Media Lab's Interactive Cinema group, is working with Singh to build common sense into video cameras. On the other side of the Media Lab, Henry Lieberman, a research scientist who works with the Software Agents Group, is using common sense to enhance e-mail programs, language translation software, even a search engine. And just outside Singh's office, the Media Lab's 'wearable computing' group is building common sense into the devices and sensors they believe many of us will be wearing in the future." From 2001 to 2001: Common Sense and the Mind of HAL. By Douglas B. Lenat. [From HAL's Legacy: 2001's Computer as Dream and Reality edited by: David G. Stork. MIT Press. The MIT Press provides an abstract online, and the author has the full-text of the article available on the Cycorp web site.] Artificial Intelligence - Help Wanted - AI Pioneer Minsky. By Kevin Featherly. Newsbytes (August 31, 2001). "It is hard to find people who want to tackle common-sense reasoning, [Minsky] said, mainly because creating common-sense responses is an enormous programming challenge." "Birth of a Thinking Machine. For 17 years, a team has been trying to develop the most sophisticated artificial intelligence system ever. This summer, the public will be able to see its work." By Michael A. Hiltzik. The Los Angeles Times (June 21, 2001) / made available by Cycorp. "Cyc already has displayed the ability to identify common-sense absurdities. 'Cyc already knows that people have to be a certain age before they're hired for a job,' Lenat says, meaning that it could clear such inaccurate entries as mistaken birth dates from corporate payroll records."
"Learner is a system which interactively acquires knowledge about the everyday world over objects. We aim to collect knowledge about everyday world which computers do not have and which is not easily obtainable with current text extraction methods. The collection is carried out both over the web and in a kiosk setting at a science museum exhibit titled 'Robots and Us'. Learner, developed by Dr. Timothy Chklovski, currently at the Interactive Knowledge Capture group at ISI [the Information Sciences Institute at USC], is poised to supercede an earlier version of Learner, the work carried out by Dr. Chklovski as PhD research at MIT." Also see this related USC press release (August 2, 2005). AITopics/ConstraintBasedReasoningArtificial intelligence - Solving problems for the real world. By Billy Defrain. Daily Nebraskan (March 21, 2005). "For a typical American, the mention of artificial intelligence may conjure up nasty images of a robot wielding a plasma rifle atop a pyramid of human skulls. Mention artificial intelligence to Berthe Choueiry, though, and she thinks of problems. Choueiry, an associate professor of computer science and engineering, conducts artificial intelligence research at the University of Nebraska-Lincoln. And out of the wide field of artificial intelligence, her research focuses on constraint processing. This involves developing techniques to solve decision problems and applying them to real world uses, Choueiry said. ... She works to generate 'solutions that hopefully apply to real world problems like resource allocation, airline times and natural language processing,' Choueiry said. Although her tools are elaborate mathematical functions, her goal is to keep them as simple as possible. 'We’d like to develop tools for you to use constraints without even thinking of them or having to learn what they are,' she said. Constraint propagation, which is Choueiry’s speciality, is just one method of reasoning for artificial intelligence. Constraint-based reasoning is a deductive process in which the program looks at a group of data by considering which responses are not acceptable. These unacceptable responses are constraints.... Choueiry said one of the most difficult aspects of constraint processing is the concept of combinatorial explosion." Constraint Satisfaction Problems: Definition of CSP - A simple example: the crossword puzzle. From Marc Torrens. Follow the links to find out what crossword puzzles have to do with CSP's. CSP & Games from Professors Tomás Lozano-Pérez & Leslie Kaelbling's Spring 2003 course, Artificial Intelligence. Available from MIT OpenCourseWare. AITopics/Creativity
Agents & Creativity. By Margaret A. Boden. "Published in the Communications of the Association for Computing Machinery, special issue on Agents (ed. D. Riecken), summer 1994." Artificial Genius. By Margaret A. Boden. Discover Magazine. (October 1996). The full text is available from the magazine's online archive. FIXED: , bgb , 10/17/08 -- http://findarticles.com/p/articles/mi_m1511/is_/ai_18693675?tag=artBody;col1 Precis of "The Creative Mind: Myths and Mechanisms". By Margaret A. Boden. [London: Weidenfeld & Nicolson 1990 (Expanded edn., London: Abacus, 1991.)] "[U]nedited preprint (not a quotable final draft) of: Boden, Margaret A. (1994). Precis of The creative mind: Myths and mechanisms. Behavioral and Brain Sciences 17 (3): 519-570. The final published draft of the target article, commentaries and Author's Response are currently available only in paper." Making Machines Creative. By Roger C. Schank & Chip Cleary. (1995). In: S Smith, T B Ward & R A Finke (eds) The Creative Cognition Approach. MIT Press. 229-247. "For much of the history of AI and cognitive science, creativity was viewed as an esoteric and perhaps somewhat magical process that was above and beyond 'normal' processing. As a result, few researchers have risked tackling it. Instead of being banished to the untouchable heights of cognition, creativity belongs squarely in its center. Far from being esoteric, creativity arises from relatively simple mental processes. Far from being magical, it depends on pre-existing, though complex, mental structures. The creative process is not above and beyond 'normal' reasoning, but rather is central to it." Computational Creativity Workshop at IJCAI-05. "This workshop will bring together researchers from AI, Cognitive Science and other related areas such as Psychology, Philosophy and Arts working on Computational Creativity, providing the opportunity to promote presentation and discussion of ongoing work in the area. The workshop should encourage cross-fertilization between the various approaches, including the study of cognitive and computational models for Creativity, and the application of current AI techniques to the development of Creative Systems. The workshop will provide a forum for identifying trends and opportunities for research on creativity and promising practices concerning the development of creative systems. This workshop is the latest in a growing list of events that have, since 1997, solidified and added rigour to the computational treatment of creative processes (symposia and workshops associated with AISB 00, ICCBR 01, AISB 01, ECAI 02, AISB 02, IJCAI 03, AISB 03, LREC 04, ECCBR 04)." AITopics/CrosswordPuzzles
Thesis: Design and Implementation of Crossword Compilation Programs Using Sequential Approaches. By Sik Cambon Jensen (1997). AITopics/DataMiningTutorial Slides on Statistical Data Mining. Authored by Andrew Moore, CMU. NOT BROKEN: , bgb , 10/17/08 Knowledge-based Scientific Discovery from Geological Databases. By C. Li and G. Biswas. (1995). "It is common knowledge in the oil industry that the typical cost of drilling a new offshore well is in the range of $30 40 million, but the chance of that site being an economic success is 1 in 10. Recent advances in drilling technology and data collection methods have led to oil companies and their ancillaries collecting large amounts of geophysical/geographical data ... Can this vast amount of history from previously explored fields be systematically utilized to evaluate new plays and prospects?" Business Intelligence - The Value in Mining Data. By Jonathan Wu. DM Review (February 2002). "Data mining can best be described as a business intelligence (BI) technology that has various techniques to extract comprehensible, hidden and useful information from a population of data. This BI technology makes it possible to discover hidden trends and patterns in large amounts of data. The output of a data mining exercise can take the form of patterns, trends or rules that are implicit in the data. ... The following are examples of practical uses of data mining and the value it provides those who use this technology to mine their data. ... Fraud Detection ... Inventory Logistics ... Defect Analysis ... Focused Hiring." AITopics/DecisionTreesSimple Tree Searches. By J. Matthews. Available from Generation 5. "This essay will cover very basic tree searches, the depth-first and breadth-first. In artificial intelligence, we use trees to represent a lot of things, from sentence structures, equations and even game states. Often, a method of searching the trees to find a specified goal is required - these algorithms are the simplest methods to do this." http://www.aaai.org/AITopics/BrokenLinks01sep08?action=edit Decision Trees. From MLnet. Explore the various algorithms and methods, and use the cross-reference link to learn about Regression Trees. AITopics/DesignWhat We Know About Learning. By Herbert A. Simon, Department of Psychology, Carnegie Mellon University. (Speech presented at the 1997 Frontiers in Education Conference.) "A characteristic of design that is special to it, besides this gradual emergence of goals, is that the largest task is to generate alternatives. There are lots of theories of decision making, a field that has been heavily cultivated by economists and statisticians. But most theories of decision making start out with a given set of alternatives and then ask how to choose among them. In design, by contrast, most of the time and effort is spent in generating the alternatives, which aren't given at the outset." AITopics/DiscourseAnalysisDiscourse Analysis Tutorial. From Dave Inman, School of Computing, South Bank University, London. Blogging for Dollars - How would you like to survey 20 million consumers in two minutes? By Justin Martin. Forbes Small Business (December 2005). "[T]o know what the masses are saying about your product, you would have to dig through 350,000 fresh daily postings on a staggering 20 million blogs worldwide.... Enter Umbria, a market research firm in Boulder that designs software to find useful consumer intelligence on the Internet. ... Another big challenge is to decipher what's on a blogger's mind. To figure out whether an opinion is strong or tepid, for example, it helps to know that 'awesome' is a stronger endorsement than 'pretty cool,' and that 'shoddy' is less damning than 'abominable.' Umbria has several employees with Ph.D.s in linguistics and artificial intelligence who are forever tweaking the software to make it better at categorizing opinions. Kaushansky claims his software can even identify sarcasm, a useful skill in the prickly blogosphere. ... The software can also estimate the author's age and gender. ... Automation is the source of Umbria's competitive edge: affordability." Local Discourse and Reference. Lecture notes from Bill Wilson, Associate Professor in the Artificial Intelligence Group, School of Computer Science and Engineering, University of NSW. "This section concerns the problem of deciding what phrases (especially noun phrases) refer to. It introduces a simple model of global discourse structure called the history list, and presents an algorithm for referent determination in simple cases." Computational Semantics Laboratory. "We are a research group at the Center for the Study of Language and Information (CSLI) at Stanford University, under the direction of Stanley Peters. We work on a number of projects which involve semantics -- the study of meaning -- at the intersection of linguistics and computer science. A unifying theme in our research is an emphasis on the role of context in determining meaning. We are particularly interested in theoretical models of communication, language, dialogue, computation, and inference which take into account the context in which these activities are occurring."
Mutual Beliefs of Multiple Conversants: A Computational Model of Collaboration in Air Traffic Control. By David G. Novick and Karen Ward, Oregon Graduate Institute of Science & Technology. In Proceedings of the the Eleventh National Conference on Artificial Intelligence, 196 - . Menlo Park, Calif.: AAAI Press. "This work develops a computational model for representing and reasoning about dialogue in terms of the mutuality of belief of the conversants. We simulated cooperative dialogues at the speech act level and compared the simulations with actual dialogues between pilots and air traffic controllers engaged in real tasks. In the simulations, addressees and overhearers formed beliefs and took actions appropriate to their individual roles and contexts. The result is a computational model capable of representing the evolving context of complete real-world multiparty task-oriented conversations in the air traffic control domain." AITopics/DramaGames of infinite possibilities. By Jonathan B. Cox. The News & Observer (January 15, 2003). "R. Michael Young, an assistant professor of computer science at N.C. State University, is working on research that might one day make video games more enjoyable. Young, 41, is studying ways to build artificial intelligence -- the ability of computers to act like humans -- into games so that users get movielike stories. With such technology, for example, a game could adjust to a player's actions and provide a different experience every time it is played. He sat down with Connect's Jonathan B. Cox to discuss his work. ... 'Specifically, the stuff I look at tries to take ideas from conventional AI [artificial intelligence], linguistics, cognitive psychology and ideas about narrative theory and look at computational models of narrative, so that you can take these computational tools that are well founded on the other theories from other disciplines and automatically create stories inside a virtual environment.'" Columbia Newsblaster - an automatic system for event tracking and summarization. Developed by members of the Columbia NLP Group.
Bookish Math - Statistical tests are unraveling knotty literary mysteries. By Erica Klarreich. Science News (December 20, 2003; Vol. 164, No. 25). "Stylometry ['the science of measuring literary style'] is now entering a golden era. In the past 15 years, researchers have developed an arsenal of mathematical tools, from statistical tests to artificial intelligence techniques, for use in determining authorship. ... For decades, computers have supported the work of experts in stylometry. Now, computers are becoming experts in their own right, as some researchers apply artificial intelligence techniques to the question of authorship." AITopics/EarthAndAtmosphericScience
Meteorological Applications of Artificial Intelligence. An extensive collection of links maintained by Bjarne K. Hansen. Cloud Physics and Severe Weather Research Division,Meteorological Research Branch,Meteorological Service of Canada.
Tornado technology improves warning time. By Shannon Womble. Savannah Morning News (August 9, 2000). "Using artificial intelligence, advanced image processing and Doppler radar data, researchers said the Warning Decision Support Systems can give Georgians an extra four to five minutes of warning time. The newer Doppler systems, commonly used by television meteorologists, only provide on average about eight minutes of warning time." AITopics/EmotionA Human Touch for Machines - The radical movement of affective computing is turning the field of artificial intelligence upside down by adding emotion to the equation. By Charels Piller. Los Angeles Times (May 7, 2002). "For the last decade, the UC San Diego psychologist has traveled a quixotic path in search of the next evolutionary leap in computer development: training machines to comprehend the deeply human mystery of what we feel. [Javier ] Movellan's devices now can identify hundreds of ways faces show joy, anger, sadness and other emotions. The computers, which operate by recognizing patterns learned from a multitude of images, eventually will be able to detect millions of expressions. ... Such computers are the beginnings of a radical movement known as 'affective computing.' The goal is to reshape the very notion of machine intelligence. ... Such devices may never replicate human emotional experience. But if their developers are correct, even modest emotional talents would change machines from data-crunching savants into perceptive actors in human society. At stake are multibillion-dollar markets for electronic tutors, robots, advisors and even psychotherapy assistants. ... Classical AI researchers model the mind through the brute force of infinite logical calculations. But they falter at humanity's fundamental motivations. ... Movellan is part of a growing network of scientists working to disprove long-held assumptions that computers are, by nature, logical geniuses but emotional dunces. ... Scientists don't foresee machines with Hal's emotional skills--or, fortunately, its malevolence--soon. But they already have debunked AI orthodoxy considered sacrosanct only five years ago--that logic is the one path to machine intelligence. It took psychologists and neuroscientists--outside the computer priesthood--to see inherent limits in the mathematical pursuit of intelligence that has dominated computer science." Films Such as 'I, Robot' Affirm Human Superiority. Duke News & Communications (July 14, 2004). "'I, Robot,' which opens Friday, revisits one of science fiction's common themes: A creation that develops a will of its own and turns against its creator. But why is that idea so appealing? It speaks to our society's deep fears that, as robots become more apparently human, we discover how machinelike we are, said Priscilla Wald, a Duke University English professor who studies how science is represented in popular culture. ... People feel anxious when they learn how easy it is to program a computer to appear to have emotions. This is possible because we follow predictable patterns, she said. 'Our sense of our uniqueness is threatened by the idea that we are predictable,' she said. 'The farther we go with artificial intelligence and the more human our machines become, the more we understand how machinelike we are. Many people find that deeply disturbing.'" Toward Empathetic Agents in Tutoring Systems. By Jessica Faivre, Roger Nkambou, and Claude Frasson. 2003. In Proceedings of the Sixteenth International Florida Artificial Intelligence Research Society Conference, 161-165. Menlo Park, Calif.: AAAI Press. Abstract: "This paper presents a way of improving computerbased with lifelike presence in learning environment. The approach combines Intelligent Tutoring Systems with research on human emotion in Cognitive Sciences, Psychology and Communication. Considering the relations between emotion, cognition and action in contextual learning, we propose an architecture of a multiagent-based instructional system in which two adaptive emotional agents have been integrated. One manifests the tutor's emotional expressions trough a 3D embodied agent, whereas the second is designed to elicit and analyse the learner's emotional experiences during the interactions with the system. We present here the system's architecture and its first implementation."
Letting your computer know how you feel. By Cliff Saran. ComputerWeekly (June 24, 2003). "Kate Hone, a lecturer in the department of information systems and computing at Brunel University, is the principal investigator in a project that aims to evaluate the potential for emotion-recognition technology to improve the quality of human-computer interaction. ... Affective computing can be defined as 'computing that relates to, arises from, or deliberately influences emotion'. A number of different types of research are encompassed within this term. For instance, some artificial intelligence researchers in the field of affective computing are interested in how emotion contributes to human and, by analogy, computer problem solving or decision making..." Norman, Donald A. 2004. Emotional Design: Why we love (or hate) everyday things.' Basic Books. Reviewed by Charles Arthur: Machines have feelings too - A new book argues that computers should be given emotions. The Independent (November 5, 2003). "Professor [Donald] Norman's thesis is that emotion - that is, gut reaction - is an essential part of our reaction to anything we interact with. Don't dismiss emotion, he argues: it's a useful function that evolution has equipped us with so that we don't have to think about everything. ... But Professor Norman goes rather further than this. He doesn't just consider what makes us react to machines and objects that we use: he takes the thinking forward to pondering the question of whether machines - such as robots and computers - should have emotions. He thinks they should, as does Professor Rosalind Pickard, an artificial intelligence expert. She told him: 'I wasn't sure [machines] had to have emotions until I was writing a paper on how they would respond intelligently to our emotions without having their own. In the course of writing that paper, I realised it would be a heck of a lot easier if we just gave them emotions.'" Picard, Rosalind. W. 1997. Affective Computing. MIT Press. "The latest scientific findings indicate that emotions play an essential role in decision making, perception, learning, and more--that is, they influence the very mechanisms of rational thinking. Not only too much, but too little emotion can impair decision making. According to Rosalind Picard, if we want computers to be genuinely intelligent and to interact naturally with us, we must give computers the ability to recognize, understand, even to have and express emotions." AITopics/Engineering
Intelligence test - Artificial intelligence is unlikely to replace engineers, says Charles Clarke, but knowledge-based tools are already playing an important part in testing and 'genetically engineering' complex design processes. By Charles Clark. Design Engineering - e4engineering.com (February 9, 2004). "Artificial intelligence is not an idea that will go down well with experienced engineers, but there's no doubt that certain software tools can take the tedium out of everyday design work. Knowledge based engineering (KBE) has been with us since the 1980s and large companies such as Boeing, BAE Systems and NASA, along with car giants Jaguar and Lotus Engineering, have bought into it. But it hasn't taken off more widely until recently, because in its traditional form it was prohibitively expensive - around £50,000 a seat just for the software was the norm."
Darwin in a Box - Are you ready for computers that speed up the process of evolution and teach themselves to think? By Steven Johnson. Discover Magazine (August 2003; Vol. 24 No. 8). "The idea is called a genetic algorithm. It creates a random population of potential solutions, then tests each one for success, selecting the best of the batch to pass on their 'genes' to the next generation, including slight mutations to introduce variation. The process is repeated until the program evolves a workable solution. ... Bill Gross and his team of inventors at Idealab in Pasadena, California, are using genetic algorithms to develop a new solar energy device (see 'Catch the Fire,' page 52). Gross believes genetic algorithms have the potential to revolutionize engineering." Smart cars - Knowledge is power...and safety. By Paul Sharke. Mechanical Engineering (March 2003). "A 2003 concept Ford Taurus blends forward collision radar, low light cameras, blind spot monitoring, lane-departure, and rear-collision warnings with telematics. A phone can block incoming calls if pre-crash sensing and navigational data tells the system the driver is too busy to answer."
ANNIE [Artificial Neural Networks In Engineering] Conference, an "international gathering of researchers interested in Smart Engineering System Design using neural networks, fuzzy logic, evolutionary programming, data mining, and artificial life." Advanced Engineering Informatics (Pre-2002 title: Artificial Intelligence in Engineering). Elsevier. "In general, researchers and commercial developers now employ a range of advanced computing techniques including, but not limited to, those originating from AI research. Although some techniques are still useful for automating mundane tasks, many are capable of enhancing the working environment and empowering engineers in ways that have not previously been possible. In all areas that involve knowledge-intensive tasks, a new philosophy that is specifically tailored to computer applications in engineering is revolutionising the field: an 'engineering informatics' is emerging."
NSPE [National Society of Professional Engineers] Ethics Cases Meet Artificial Intelligence. Engineering Times (July 2001). "Over the last several years, researchers at the University of Pittsburgh have been using NSPE's Board of Ethical Review cases in a rather unique way. Researchers Bruce McLaren and Kevin Ashley are not using the cases to directly teach students about engineering ethics or moral reasoning. Rather, they have been using the cases in research aimed at advancing artificial intelligence. ... [T]heir research attempts to build computational models of the reasoning process with cases and examples in domains such as law and practical ethics. The research aims to develop computational models that facilitate retrieval of relevant information and are used in tutoring systems that help students learn to reason by using cases." Applications of Artificial Intelligence in Engineering XIII. Editors: G. Rzevski, Brunel University, UK, R.A. ADEY, Wessex Institute of Technology, UK and P. NOLAN, National University of Ireland, Galway. http://www.aaai.org/Library/Magazine/vol21.php#Winter AITopics/FilteringEspion carving niches in e-mail security. By Ted griggs. The Advocate & WBRZ News 2 (June 9, 2006). "Espion International, a local e-mail security firm, hopes to make its reputation by providing the health-care industry with something the federal government now demands: privacy and protection for patient information. ... Espion International’s artificial intelligence algorithm, which performs many of the functions that normally require a person, monitors incoming and outgoing e-mail. The program detects anything considered personal information, from Social Security numbers to insurance policy numbers, then checks to see if those messages also contain medical information. ... Companies and consumers will spend close to $4 billion this year on anti-spam, anti-virus and e-mail security, and the amount is growing by around 25 percent per year, according to the Ferris Group, a San Francisco-based market and technology research firm." Information Filtering Resources. From the Information Filtering Project at the University of Maryland. "This page lists all known internet-accessible information filtering resources." SurfControl - Beyond Business interview on CNNFN's Money & Markets television broadcast (October 2, 2002 at 5PM EST). Cable News Network's CNNFN. "Francis: The current corporate crime wave and the central role of e-mail as evidence has companies clamoring for more sophisticated technology to identify all kinds of messages now. ... Hays: Joining us now with an inside look is Steve Purdham, CEO of SurfControl, a company that makes e-mail filtering technology. ... Francis: Now you're now employing a technology we call Neural Network technology, often used by credit card companies to spot patterns of fraud that you might not see with a naked eye. How does that work when it comes to e-mail? It's more than just looking for a dirty word here or a racial epithet there? Purdham: Yes. Absolutely. Neural Networks is a new type of technology that helps us be able to look at the fingerprint in an e-mail, looking for the - for example, if you're looking for the word 'breast', that doesn't actually say it's a sex site, it could be a medical site or it could be a medical e-mail or it could be a recipe, for example. So you have to look at things in context. An artificial intelligence, neural networks actually allows you to build a fingerprint so that the fact that the word 'breast' appears doesn't mean there's a bad e-mail. It means it actually could be a risk and therefore you go down the part of the chain." AITopics/Fraud
Inspired by immunity - By developing programs that mimic some of the functions of the immune system, computer scientists are tackling problems from fighting fraud to controlling robots. By Erica Klarreich. Nature 415, 468 - 470 (January 31, 2002). NASD Regulation's Advanced Detection System Wins Awards From Smithsonian, Data Warehousing Institute, and Artificial Intelligence Association. Press release from the National Association of Securities Dealers, Inc. (NASD¨). September 15, 1998. "ASD Regulation, Inc. announced today that its Advanced Detection System (ADS) has recently won three prestigious awards in recognition of its superior technology and ability to help deter fraud and guard marketplace integrity. ... ADS is a market surveillance, data mining, and fraud/violative behavior detection software package that monitors Nasdaq¨ for potential late-trade reporting, market integrity, and best execution violations. The system combines data visualization, time sequence pattern matching, rule-pattern matching, and data mining in a single application that looks for patterns or practices of potentially violative behavior." Signs of Fraud Go Beyond Signature - Credit Card Companies Use Artificial Intelligence to Thwart Thieves. By Margaret Webb Pressler. The Washington Post (July 21, 2002; Page H05). "As it turns out, however, credit card companies no longer rely on retail clerks to catch the crooks. ... 'We're at a level whereby we can understand with artificial intelligence . . . the potentially fraudulent transactions,' said Raf Sorrentino, vice president of risk management for First Data Corp., one of the country's biggest providers of credit card processing and payment services. Credit card fraud costs the industry about a billion dollars a year, or 7 cents out of every $100 dollars spent on plastic. But that is down significantly from its peak about a decade ago, Sorrentino says, in large part because of the powerful technology that can recognize unusual spending patterns." AI Technologies to Defeat Identity Theft Vulnerabilities. By Latanya Sweeney, The Laboratory for International Data Privacy (also known as the "Data Privacy Lab") at Carnegie Mellon University. AAAI Spring Symposium, AI Technologies for Homeland Security, 2005. VISA EU Launches New Advanced Fraud Detection Tool. System to deliver significant increase in fraud detection rates. VISA EU press release (December 29, 2003). "Visa Intelligent Scoring of Risk (VISOR) is an advanced neural network system that scrutinises card transactions to deliver a highly accurate risk score by analysing the spending behaviour of each cardholder along with the profile of each merchant."
AITopics/FuzzyLogic
International Fuzzy Systems Association. "The International Fuzzy Systems Association (IFSA) is a worldwide organization dedicated to the support, development and promotion of the fundamental issues of fuzzy theory related to (a) sets, (b) logics, (c) relations, (d) natural languages, (e) concept formation, (f) linguistic modeling, (g) vagueness, (h) information granularity, etc. and their applications to (1) systems modeling, (2) system analysis, (3) diagnosis, (4) prediction and (5) control in decision support systems in management and administration of human organizations as well as electro-mechanical systems in manufacturing and process industries." AITopics/GeneticAlgorithms
The Hitch-Hiker's Guide to Evolutionary Computation: A list of Frequently Asked Questions (FAQ). Jörg Heitkötter and David Beasley, eds. (2000). Questions include What's a Genetic Algorithm (GA)? and What's Genetic Programming (GP)? Genetic Algorithm Optimizer. From the Artificial Intelligence Lab at the University of Arizona. Marshall Ramsey's introductory demo allows you to view the graphical version of the genetic algorithm described in the text. An Introduction to Genetic Algorithms In Java. By Michael Lacy. Java Developer's Journal (Vol. 6, Issue 3; March 1, 2001). "In the January issue of JDJ (Vol. 6, issue 1) I introduced a technique born in the AI community that uses concepts from biological natural selection to solve complex and often highly nonlinear optimization problems encountered in computer science - the genetic algorithm. I examined the building blocks of genetic algorithms and why java is well suited to their implementation. This month I'll discuss the details of a simple genetic algorithm implementation in the hopes that your curiosity will be sparked to pursue further investigation." A Fast TSP solver Using A Genetic Algorithm. In this TSP demo, you can place the cities on the map! From The University of Texas at Arlington's Department of Computer Science and Engineering. GA Archives. "The Genetic Algorithms Archive is a repository for information related to research in genetic algorithms and other forms of evolutionary computation. Available from this site are past issues of the GA-List digest, source code for many GA implementations, and announcements about GA-related conferences. Also, links are given to many interesting sites around the World with material related to evolutionary computation. This archive is maintained by Alan C. Schultz at The Navy Center for Applied Research in Artificial Intelligence." IlliGAL: The Illinois Genetic Algorithms Laboratory. "[W]e study nature's search algorithm of choice, genetics and evolution, as a practical approach to solving difficult problems on a computer." Important Genetic Algorithm Information Sites from the Los Alamos Genetic Algorithms Niche. Maintained by Hillol Kargupta. "NaturalMotion's Active Character Technology (A.C.T.) is based on Oxford University's research on the control of human and animal body motions. In essence, we build a physical, biomechanically-realistic model of a character (e.g. a human or a dinosaur), implant an appropriate brain structure (usually a neural network), and use optimisation techniques (such as artificial evolution) to create the desired behaviour."
AITopics/Go
All Fired Up About Intelligent Detectors. "Thanks to developments in smoke and fire detection technologies, buildings are becoming increasingly automated. Artificial intelligence is a key factor." From Siemens AG. Heading for Disasters. By Barbara Forster. Computerworld (September 4, 2000). "The next generation of search-and-rescue workers looking for victims in buildings that collapsed in earthquakes or explosions will slither through eight-inch ducts, navigate dark, rubble-strewn corridors and be tossed into third-floor windows. They will be impervious to pain, fire and water. They will be robots - autonomous and mobile. Industrial robots have been used successfully for decades, but their descendants will be a relatively new breed with sufficient intelligence to carry out complex tasks, including planning and decision-making in unstructured and dynamic environments where missions are time-critical." Search-Rescue Robots Test Their Mettle in Tournaments - Researchers Aim to Improve Vehicles' Skills for Real-Life Use. By Guy Gugliotta. Washington Post TechNews (May 30, 2003). "Ten years ago, no one had tried to use robots for search and rescue, but by 2001 researchers had enough expertise to deploy robotic vehicles with some success to search through rubble at the World Trade Center and the damaged buildings around it. Now robots compete annually in two international search-and-rescue tournaments, measuring their progress in diabolically difficult arenas designed by the National Institute of Standards and Technology (NIST). RoboCup Rescue: A Grand Challenge for Multiagent and Intelligent Systems. By Hiroaki Kitano and Satoshi Tadokoro. AI Magazine 22(1): Spring 2001, 39-52. "In this article, we present a detailed analysis of the task domain and elucidate characteristics necessary for multiagent and intelligent systems for this domain. Then, we present an overview of the RoboCup Rescue project." CHEMREG: Using Case-Based Reasoning to Support Health and Safety Compliance in the Chemical Industry. By Kirk D. Wilson. AI Magazine, 19(1): Spring 1998, 47-58. "CHEMREG is a large knowledge-based system used by Air Products and Chemicals, Inc., to support compliance with regulatory requirements for communicating health and safety information in the shipping and handling of chemical products. This article concentrates on one of the knowledge bases in this system: the case-based reasoner. The case-based reasoner addresses the issue of how proper communication of public health and safety information can be ensured while rapid and cost-effective product evaluation is allowed in the absence of actual hazard testing of the product. CHEMREG generates estimates of hazard data for new products from similar products using an existing relational database as a case library." Biomedical Security Institute. "BMSI has a two-pronged approach: 1.) Development of a prototype computer-based surveillance, analysis and communication systems infrastructure to provide early warning of naturally occurring disease outbreaks and terrorist attacks employing biological pathogens. It will perform continuing real-time data mining and analysis of selected data streams (such as electronic medical records and microbiology laboratory results) for sentinel events or situations. ... 2.) A research program that integrates the latest research and technology in public health, biomedical sciences and biomedical informatics, including: ... Intelligent systems, data mining, artificial intelligence, bioinformatics and early detection/early warning computer-based surveillance systems...." Also see:
CREATE, the Center for Risk and Economic Analysis of Terrorism Events, "is an interdisciplinary national research center based at the University of Southern California and funded by the Department of Homeland Security. The Center is focused on risk and economic analysis of the U.S. and comprises a team of experts from across the country, including partnerships with New York University and the University of Wisconsin at Madison."
Fetch II - Counter Mine Intelligence. From iRobot. "The Fetch II robots perform their tasks autonomously but with the supervision of a single operator. Behavior Based intelligence in each Fetch II enables it to navigate through real world terrain autonomously, using a relative coordinate positioning system and task-specific sensors mounted on a robust mobility platform. The Behavior Based software mediates robot-robot interference within the swarm and supports mutual cooperation among them."
UrbanSearch and Rescue at the Perceptual Robotics Laboratory, University of South Florida. Lots of exciting information awaits you at this site including their collection of FAQs where you'll find answers to questions such as "What tasks can robots do in USAR?" AITopics/ImageUnderstanding
Finding people and animals using body plans and action plans. David Forsyth and Margaret Fleck, The Computer Science Division, University of California, Berkeley. "A body plan is a sophisticated model of the way jointed objects are put together; at present, we have two programs that can find objects using body plans. One program can tell, quite accurately, whether a picture contains a naked person or not. Another program can tell, again quite accurately, whether a picture contains a horse. "
An Intelligent Framework for Image Understanding. By Ahmed E. Ibrahim. "The goal of image understanding system often involves the identification of objects in images and the establishment of the relationships among the objects. This transformation of signals (the images) to symbols (the interpretation) in the visual domain is one of the most important and most difficult task in artificial intelligence."
Be sure to check out their video demos! Analysis and Recognition of Walking Movements. James Davis and Stephanie Taylor. International Conference on Pattern Recognition, Quebec City, Canada, August 11-15, 2002, pp. 315-318. AITopics/InductionInductive Learning Techniques: definition and example. From the MLnet Online Information Service. "In inductive learning, knowledge is compiled by generalising patterns in factual experience. ..." AITopics/InformationRetrievalAndExtractionInformation Service Agent Research. "The Information Service Agent Lab at Simon Fraser University develops novel techniques for interactive information gathering and integration. The research applies artificial intelligence planning and learning techniques and database technologies to create knowledge bases from large collections of dynamically changing, potentially inconsistent and heterogeneous data sources, permitting users access to information at the right abstraction level." Projects. Software Agents Group, MIT Media Lab. Wide-ranging approaches to information retrieval that include user profiling, information filtering, privacy, recommender systems, communityware, negotiation mechanisms and coordination.
Is There an Intelligent Agent in Your Future? By James A. Hendler (1999). (This wonderful paper received the AAAI-2000 Effective Expository Writing Award.) Savvysearch... By Adele Howe, and Daniel Dreilinger (1997). AI Magazine 18 (2): 19-25. Description of a metasearch engine that learns which search engines to query. In Search of a Lost Melody - Computer assisted music: identification and retrieval. By Kjell Lemstrom. Finnish Music Quarterly Magazine 3-4/2000. The Revolution in Legal Information Retrieval or: The Empire Strikes Back. By Erich Schweighofer (1999). The Journal of Information, Law and Technology 1999(1). "The issue is how to deal with the Artificial Intelligence (AI)-hard problem of making sense of the mass of legal information." Text Mining Technology - Turning Information Into Knowledge. A white paper from IBM (1998), Daniel Tkach, editor.
HP SpeechBot - audio search using speech recognition. From Hewlett-Packard.
MARVEL: "The Intelligent Information Management Department at IBM Research is developing a multimedia analysis and retrieval system called MARVEL. MARVEL helps organize the large and growing amounts of multimedia data (e.g., video, images, audio) by using machine learning techniques to automatically label its content. The system recently won the Wall Street Journal 2004 Innovation Award in the multimedia category." A demo is available. "NewsInEssence is a system for finding and summarizing clusters of related news articles from multiple sources on the Web. It is under development by the CLAIR group at the University of Michigan." You can see it in action here. SOPHIA Search Ltd: "established to exploit exciting new technology conceived and developed at the University of Ulster, Northern Ireland in partnership with St. Petersburg State University, Russia ." As stated on their How SOPHIA Searches page: "By automatically discovering themes present in the collection and breaking them down into topics SOPHIA creates intuitive groupings (clusters) of semantically related content and presents these to users as the result of a search." AITopics/IntelligentTutoringSystemsArtificial intelligence alive and well . The University of Auckland News (January 19, 2005). "While statistics students at The University of Auckland are taking a break from studies for summer, their new 'teacher' can’t wait for the new semester to begin. Maria, an assistant teacher in Statistical Interference, is an unusual individual. She looks to be in her mid-twenties but her age, she says, cannot be computed in human years. With a vocabulary of 203,000 words, a repertoire of 106,000 grammatical rules and 118,000 rules of logical inference, Maria is capable of conversation at quite a complex level. Maria is a robot, or artificial intelligence entity, created over two years of intense work and study by Shahin Maghsoudi, a PhD student and member of the Artificial Intelligence Group in the Faculty of Science. As part of his Masters degree in Computer Science, Shahin embarked on a project to create virtual robots which could be used as teaching assistants, helpdesk operators and web-based marketing assistants." Intelligent Tutoring Systems. A brief introduction by Eric Thomas. Part of San Diego State University's Encyclopedia of Educational Technology. The Roles of Artificial Intelligence in Education: Current Progress and Future Prospects. David McArthur, Matthew Lewis, and Miriam Bishay. (1993) RAND DRU-472-NSF. A very good overview with lots of basic information about intelligent tutoring systems. A teacher who gets by on artificial intelligence" (International Herald Tribune and Israeli Haaretz Daily, 12/20/98) and "Intelligent agents help humans learn from computers" (CNN Interactive, 8/25/97) are just two of the exciting articles about Pedagogical Agents and Guidebots that you'll find at CARTE's very informative site. [CARTE = The Center for Advanced Research in Technology for Education which is part of the Information Sciences Institute at the University of Southern California.] Be sure that you don't miss the demos and videos, or their many pedagogical agents and guidebots (see: research and projects). Talking Up a Good Game - Computer Simulation to Stimulate Soldiers to Speak in Tongues. By Paul Eng. ABCNEWS.com (March 9, 2004). "The first part of the game, says [Lewis] Johnson, acts as basically an 'intelligent tutoring' program.' ... But what makes the program really 'intelligent' are the computer-generated and -controlled characters, such as a virtual village leader and a virtual 'team member' that acts as an in-game guide. These game characters are programmed to react in ways that are unique to each individual user." Encouraging Student Reflection and Articulation using a Learning Companion . By Bradley Goodman, Amy Soller, Frank Linton, and Robert Gaimari (1998). International Journal of Artificial Intelligence in Education, 9(3-4). "The goal of the research presented in this paper is to promote more effective instructional exchanges between a student and an intelligent tutoring system The approach taken to meet this goal involves providing a simulated peer as a partner for the student in learning and problem solving. The learning companion described in this paper enhances learning by initiating a dialogue with a student forcing reflection and articulation on the student's learning."
CIRCLE: Center for Interdisciplinary Research on Constructive Learning Environments. "CIRCLE is an NSF-funded research center located at the University of Pittsburgh and Carnegie Mellon University, with multiple partnerships among schools, industries and other research institutions. CIRCLE's mission is to determine why highly effective forms of instruction, such as human one-on-one tutoring, work so well, and to develop computer-based constructive learning environments that foster equally impressive learning." Be sure to follow the links to "Projects" for that's where you'll find systems such as: The EPSILON [Encouraging Positive Social Interaction while Learning ON-Line] Project at the Learning Research and Development Center, University of Pittsburgh "is an interdisciplinary effort to provide dynamic, adaptive support for on-line learning communities. The support, in the form of an intelligent software agent, will focus on helping students improve their social and communication management skills. ... The EPSILON software will be driven by a computational model of effective learning interaction. The project will explore methods for dynamically analyzing on-line interaction during structured learning activities. Artificial Intelligence techniques will be employed for analyzing, studying, and characterizing on-line interaction." The project consortium members are: Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, European Research and Project Office GmbH, The University of Edinburgh, Technische Universiteit Eindhoven, Mathematisches Institut, University of Glasgow, Universidad de Malaga , Ernst Klett Verlag, and Universität des Saarlandes. Pedagogical Agents and Learning Systems (PALS) Research Group members at the Center for Research of Innovative Technologies for Learning (RITL), Florida State University, "investigate the affordances and constraints of animated pedagogical agents within eLearning environments.What is a 'pedagogical agent?' (As stated by W. Lewis Johnson): Pedagogical agents are autonomous agents that support human learning, by interacting with students in the context of interactive learning environments. They extend and improve upon previous work on intelligent tutoring systems in a number of ways. ..."
Murray, Tom. 1999. Authoring Intelligent Tutoring Systems: An analysis of the state of the art. International Journal of Artificial Intelligence in Education (1999), 10: 98-129. "This paper consists of an in-depth summary and analysis of the research and development state of the art for intelligent tutoring system (ITS) authoring systems. A seven-part categorization of two dozen authoring systems is given, followed by a characterization of the authoring tools and the types of ITSs that are built for each category. An overview of the knowledge acquisition and authoring techniques used in these systems is given. A characterization of the design tradeoffs involved in building an ITS authoring system is given. Next the pragmatic questions of real use, productivity findings, and evaluation are discussed. Finally, I summarize the major unknowns and bottlenecks to having widespread use of ITS authoring tools." AITopics/Interviews
Bruce Buchanan. Interviewed by John Aronis for Links, the newsletter of The Department of Computer Science at the University of Pittsburgh (Spring 2003; pages 2 - 4)." While working in the Stanford Artificial Intelligence Laboratory, Bruce and his collaborators made important contributions to artificial intelligence. Their assertion -- obvious in retrospect like most great ideas -- was that knowledge is important for intelligent behavior. They drove this point home with a series of programs that embodied the knowledge of scientific and medical experts -- sometimes rivaling or surpassing their abilities -- and the creation of an industry centered around expert systems." Henrik Christensen. Man and machine - Scholar envisions new devices to help extend the reach of the human race --- tirelessly. By Bill Husted. The Atlanta Journal-Constitution & ajc.com (April 23, 2006). "Once a week, a robot handles the vacuuming for Henrik Christensen. It does a good job but --- like a lot of housekeepers --- sometimes misses dirt in the corners. Christensen occupies the newly created KUKA Chair of Robotics at Georgia Tech's College of Computing. And he practices what he preaches with the robotic housekeeper. ... Q: Is there a place for that stereotypical robot, too? The machines that work around the house? ... Q: One of the public fears, when it comes to robots, is that they'll eventually cost people jobs. Do you think that's a rational fear? ... Q: What are the new developments in robotics? ..."
Michael Hawley. In His Own Words. A scientist at MIT's Media Lab reveals the true nature of a college of arts and sciences As told to Calvin Fussman. Discover Magazine ( September 2003; Vol. 24, No. 9). "I'm kind of a perfect mix of my parents. My dad was an electrical engineer at Bell Laboratories in Murray Hill, New Jersey. ... My mom was into English literature and music. I was really lucky to have the yin and the yang. .... I wound up at MIT as a protégé of Marvin Minsky at the Media Lab. I lived in Marvin's attic for a year. It was wonderful, almost indescribable. Marvin's house was like F.A.O. Schwarz after the bomb went off. There was a trapeze hanging in the living room. You'd open the refrigerator and find seal meat stored on a shelf for the dogs of a visiting Iditarod champion. ... When your job is to invent new possibilities for computers...."
Kraftwerk. Man-Machines of Loving Grace - Kraftwerk return! By Jay Babcock. LA Weekly (June 3 - 9, 2005). "Next Tuesday, German electronic-music pioneers Kraftwerk will perform in Los Angeles for the first time since their now-legendary show at the Hollywood Palladium in 1996. ...We all know Kraftwerk songs -- odes to transportation like 'Autobahn' and 'Trans-Europe Express,' future/now manifestoes like 'Man/Machine' and 'The Robots' -- but it’s in the live context, where the songs are joined to specially designed graphics, that Kraftwerk achieves a purity of all-encompassing vision that secular music rarely touches. It’s all about rapture, and an interaction with -- or longing for -- a relationship with something other than human. On the telephone, Ralf Hutter -- co-founder of Kraftwerk with Florian Schneider, and now approaching 60 years of age -- is helpful and deliberate, like a professor pleased to have a visitor who’s interested in his research on an obscure subject. L.A. WEEKLY: There's a bumper sticker that says 'Drum machines have no soul.' Do you think that is true? ... Would you consider the Kraftwerk concept to be basically optimistic about the relationship between man and machine? ... There’s an almost universal fascination with machines and computers, but at the same time, isn't there a cultural fear of the future, of machines taking over? A fear of cyborgs? ... What do you think about artificial intelligence? Do you think it's possible that a machine can become sentient? ... When you let machines play at concerts -- especially when there are actual robot versions of Kraftwerk onstage in place of the humans -- when you do that, and the audience applauds at the end of the song, what are the people applauding for?..."
Tod Machover. Interview. The composer and electronic instrument maker from MIT's Media Lab discusses his latest project: the Brain Opera. Scientific American (August 1996).
Rosalind Picard. Interviewed in First Monday. "Rosalind Picard is NEC Development Professor of Computers and Communications and Associate Professor of Media Technology at MIT. ... Her research interests include affective computing; texture and pattern modeling; and browsing and retrieval in video and image libraries. Her most recent book, Affective Computing, was just published by MIT Press...." June 1999 interview (in English) conducted at an authors' colloquim at the University of Bielefeld. An excerpt: "Actually, I think you misunderstand my position a little bit in the way you pose the question. I do not claim that all forms of artificial intelligence and cognitive science are based on philosophical errors. Rather I criticize only what I call strong artificial intelligence, or strong AI, and the corresponding branch of cognitive science, the branch of cognitive science that accepts strong AI. Strong AI is the view that the appropriately programmed digital computer thereby necessarily has a mind in exactly the same sense that you and I have minds."
Carnegie Mellon's Women@SCS: Interviews with Women in Computer Science. Generation 5 Interviews: a wonderful (and growing) collection of interviews conducted with Tim Crane, Teuvo Kohonen, Steven Levy, Marvin Minsky, Melaine Mitchell, Roger Schank and others. The Charles Babbage Institute (CBI), University of Minnesota, Minneapolis, Oral History Collection. Abstracts of the interviews and most of the transcripts are available online. Talking Nets: An Oral History of Neural Networks. Anderson, James A., and Edward Rosenfeld, editors. 1998. Cambridge, MA: MIT Press/Bradford Books. Interviews with founders of the field of study, including how these scientists from different disciplines became interested in neural networks, and what future developments they see. Excerpts are available online. AITopics/KnowledgeManagementApplied Artificial Intelligence and the Management of Knowledge. By Colquhoun-John Ferguson & Scott Goldie, Department of Management & Marketing University of Paisley. Bristol Business School Teaching and Research Review, Issue 3, Summer 2000. "Our current research addresses the question of how artificial intelligence (AI) tools may facilitate the organising, disseminating, storing and interpreting of knowledge. Two (AI) techniques have formed the focus for our research with the aim of combining these techniques into a hybrid system to manage the interpretation of corporate data and information for use by product designers: case -based reasoning and data mining."
, and in these articles:
Also available from the ResearchIndex. "As employees turn over in today's overheated job market, organizations are likely to lose access to large quantities of critical knowledge. Can we create a system that will capture company-wide knowledge and make it widely available to all its members?" "SAGE [Searchable Answer Generating Environment] is a Knowledge Management (KM) system that aims to create the first repository of experts in the State of Florida. Currently, each of the State Universities in Florida maintain information concerning funded research, but these databases are disparate and disjoint. The SAGE application creates one single web-enabled repository which can be searched in a number of ways including RESEARCH TOPIC, INVESTIGATOR NAME, FUNDING AGENCY, or UNIVERSITY."
Tutorial: AI Techniques for Knowledge Management. By S. Decker & S. Staab. ECAI-2000 Tutorial Berlin, August, 21-22, 2000. AITopics/LanguagesKnowledge Representation: Concepts & Semantic Networks. From the Department of Computing and Mathematics, Faculty of Informatics, University of Ulster. "[S]emantic networks are an attempt to model the way we think about concepts, and have been used by psychologists and computer scientists alike in trying to explain, and simulate, intelligent behaviour." What is A Knowledge Representation? Davis, Randall, Howard Shrobe, and Peter Szolovits. 1993. AI Magazine 14 (1): 17-33. [Also available in HTML] "What is a knowledge representation? We argue that the notion can best be understood in terms of five distinct roles it plays, each crucial to the task at hand: * A knowledge representation (KR) is most fundamentally a surrogate, a substitute for the thing itself, used to enable an entity to determine consequences by thinking rather than acting, i.e., by reasoning about the world rather than taking action in it. * It is a set of ontological commitments, i.e., an answer to the question: In what terms should I think about the world? * It is a fragmentary theory of intelligent reasoning, expressed in terms of three components: (i) the representation's fundamental conception of intelligent reasoning; (ii) the set of inferences the representation sanctions; and (iii) the set of inferences it recommends. * It is a medium for pragmatically efficient computation, i.e., the computational environment in which thinking is accomplished. One contribution to this pragmatic efficiency is supplied by the guidance a representation provides for organizing information so as to facilitate making the recommended inferences. * It is a medium of human expression, i.e., a language in which we say things about the world." A Framework for Representing Knowledge. By Marvin Minsky. MIT-AI Laboratory Memo 306, June, 1974. Reprinted in The Psychology of Computer Vision, P. Winston (Ed.), McGraw-Hill, 1975. Shorter versions in J. Haugeland, Ed., Mind Design, MIT Press, 1981, and in Cognitive Science, Collins, Allan and Edward E. Smith (eds.) Morgan-Kaufmann, 1992. "Here is the essence of the theory: When one encounters a new situation (or makes a substantial change in one's view of the present problem) one selects from memory a structure called a Frame. This is a remembered framework to be adapted to fit reality by changing details as necessary. A frame is a data-structure for representing a stereotyped situation, like being in a certain kind of living room, or going to a child's birthday party. Attached to each frame are several kinds of information. Some of this information is about how to use the frame. Some is about what one can expect to happen next. Some is about what to do if these expectations are not confirmed." AITopics/LawFor an interesting insight into the "birth date" of AIL (Artificial Intelligence and Law), see footnote 3 on page 1366 of Peter Tiller's Introduction: A Personal Perspective on "Artificial Intelligence and Judicial Proof (Volume 22; page 1365) in the Artificial Intellegence and Judiciary Proofs symposium issue of the Cardozo Law Review (July 2001). Artificial Intelligence and the Law. Chapter 13, Technology & The Law, 1999 Final Report of the
"The Law Technology Journal (LTJ) was published by the CTI Law Technology Centre from 1991 until 1996. It was superceded by a web journal, the Journal of Information Law and Technology (JILT). All issues of the LTJ are on this web site."
Putting litigation support on trial. By Julian Baker. Legal Week (September 4, 2003). "Litigation support technology has moved beyond the basic indexing of documents and there are now an array of technology tools available which can be used to assist litigators in preparing the case for court and in the courtroom itself. This technology can be applied to cases across the size and complexity spectrum. Potential costs savings and efficiencies mean that clients will come to expect the use of this technology as an industry norm. ... An interesting development is the use of artificial intelligence-based software to automatically identify common themes and concepts within a large quantity of documents with only a minimal amount of information being indexed manually." New database search for law firms. By Roger Harris. Scripps Howard News Service / available from the Albuquerque Tribune (Novewmber 17, 2002). "Scouring through millions of e-mails, memos, letters and other documents looking for information critical to a case is not any lawyer's idea of fun. The search can take months and cost lots of money. At least, it used to. Now, thanks to new search technology developed by DolphinSearch Inc., a privately owned Ventura company, document searching is easier, faster, cheaper and more accurate. The patented technology uses artificial intelligence to search for context and meaning, much like a human, said CEO Andrew Kraftsow. ... In his research, [Herbert] Roitblat discovered that the way dolphins recognize objects in the ocean is similar to how humans use context to determine the meaning of a word. Based on this discovery, he built a computer using neural network model to mimic the dolphin's search capabilities. ... The Florida law firm of Carlton Fields saved a client more than $125,000 in fees because DolphinSearch shortened the document research time by months." Teaching Artificial Intelligence to Law Students. By Dan Hunter. (1994). Law Technology Journal: Vol 3, No 3. "[T]eaching artificial intelligence in law schools is extremely rewarding and not as difficult as it might appear. It does require however a recognition of the difficulties that some students face, and how some fundamental tensions can give rise to difficulties in teaching these types of 'innovative' subjects to law students." Artificial intelligence - threats and opportunities. Legal IT (October 6, 2005). "The future may be electronic, says Ian Pearson, futurologist for BT, but even in a world of conscious computers and artificial intelligence, lawyers will still be in huge demand."
Technology and the Future of Legal Services. By John A. Tull. American Bar Association Center for Professional Responsibility (November 1999). "This paper considers the rapid course of that change and some aspects of its potential impact on legal services for low income persons. ... Artificial intelligence may also bring dramatic changes for how legal services advocates practice law. The repetitive cases common to many areas of legal services practice might very well lend themselves to initial analysis by artificial intelligence. ... Artificial intelligence (and its cousin, the neural network) is what its name implies: Machines that are capable of analyzing data to reach a conclusion regarding their significance and determining the next steps that should be taken in response. Perhaps no other change feels quite so threatening to many lawyers. After all, such analysis is what lawyers do. On the other hand, artificial intelligence may significantly streamline the practice of law. ... Artificial intelligence is already being used in 'smart' document building, preparing necessary papers for an attorney B or directly for a client. For courts, it could present the possibility of requiring the parties to litigation to subject their claim to a computer analysis on the question of liability and possible damages, as a nudge to responsible settlement. For a client, it may mean accessing a web site to obtain a preliminary analysis of a specific legal problem or information about rights and responsibilities in specific circumstances." "The Joseph Bell Centre for Forensic Statistics and Legal Reasoning has been set up to evaluate, present and interpret evidence. The Centre draws on skills in statistics, law and artifical intelligence from the University of Edinburgh, Glasgow Caledonian University and the Lothian and Borders Police Force. Researchers from Australia, Belgium, England and the United States are collaborating with the Scottish researchers." International Association for Artificial Intelligence and Law. "IAAIL is an organization devoted to promoting research and development in the field of AI and and Law with members throughout the world. IAAIL organizes a bi-annual conference (ICAIL), which provides a forum for the presentation and discussion of the latest research results and practical applications and stimulates interdisciplinary and international collaboration."
Project EAGLE: "A research and development initiativeto use advanced computer technology to help makeUK employment rights more accessible to people who need advice. Aims: to enable generalist advisers to deal with employment law enquiriesby using a state-of-the-art interactive program, which emulates the knowledge,experience and even the approach of specialists in employment rights. Partnership: a joint project between the Legal Services Commission,and the Citizens Advice Bureaux of Bedworth, Warwickshire, andStoke-on-Trent from September 2002 to December 2005."
Kagayama, Shigeru. 1995. The Fundamentals of Expert Systems on Tort in Japan. "In this paper I will deal with the subject of automated legal reasoning research in Japan. This type of research has come to be called 'legal expert system' research. The subject will be treated in a concrete manner using Japanese tort law as an example." Rissland, Edwina L. Review of An Artificial Intelligence Approach to Legal Reasoning, by Anne vonder Lieth Gardner. Cambridge, Massachusetts: The MIT Press, 1987, pp. 193. Harvard Journal of Law and Technology Volume 1, Spring 1988. AITopics/LawEnforcementBSc (Hons) Forensic Computing. Designed by Dr. Giles Oatley, Senior Lecturer, School of Computing and Technology, University of Sunderland "The degree provides an understanding of criminology, types of forensic data and appropriate analysis techniques, and how to operationalise findings in decision support software based upon advanced artificial intelligence technologies and 'industry entrance level' computer programming skills. This degree is unique among the UK, and spans the disciplines of criminology (with some aspects from forensic psychology), chemistry / pharmacology and computing. This broad range is necessary for this challenging and quickly growing area of analysis of forensic data. With the popularizing of this subject by such TV programs as 'CSI-Miami' and the emphasis from the Home Office upon technology-based solutions, this degree course will provide the tools necessary for a very interesting and enriching career."
Tucson cops, local software to help in D.C. sniper probe. By Larry Copenhaver. Tucson Citizen (October 23, 2002). "Federal officials asked Tucson police for help in using the system, COPLINK. It allows investigators to feed leads and other data on a case into a computer system, and a software program then provides advanced analytical and search capabilities for investigators. ... HOW COPLINK WORKS: The system digs through databases and reports to pick out connections among suspects, vehicles, crimes, locations and other data. It gives police the capability, with limited information, to find investigative leads they don't get anywhere else. Simply put, it searches separate databases at various agencies and returns information based on a query." >> Photo caption: "Hsinchun Chen shows Tucson police Detective Tim Petersen (right) how to use COPLINK software in January 2001. Chen led a University of Arizona Artificial Intelligence Lab team in developing COPLINK software. ..." No future for crooks. By Mark Cowan. Evening Mail / available from icBirmingham (October 12, 2002). "Police could soon be detecting crime in the West Midlands before it actually happens in an echo of hit Hollywood movie Minority Report. Police are developing computer software which could predict where crooks strike next. Using the latest in artificial intelligence, the digital detective would examine a criminal's modus operandi and suggest a future pattern of offending. ... The 'Tomorrow's World' idea is the latest development for the ground-breaking Flints II crime-busting computer pioneered by West Midlands Police."
Testimony of John Roth, Chief of Criminal Division's Asset Forfeiture and Money Laundering Section, Department of Justice, before the Committee on Government Reform, Subcommittee on Criminal Justice, Drug Policy, and Human Resources hearing: Terrorist Financing and Money Laundering Investigations: Who Investigates and How Effective are They (May 11, 2004). "Money laundering constitutes a serious threat to our communities, to the integrity of our financial institutions and to our national security. Behind every dollar of dirty money in need of laundering is a trail of victims.... Money laundering enforcement may be unique, because it requires the participation of a broad spectrum of government agencies as well as the private sector. ... Although the coordination challenges are great, we meet the challenge in a number of ways. The Department of Justice assists in coordination though a number of means. I will name a few of the more formal mechanisms we use. ... - Financial Crimes Enforcement Network (FinCEN): FinCEN is a valuable component of our efforts to use Bank Secrecy Act information effectively. FinCEN digests and analyzes SAR reports and conducts financial data inquiries for all agencies. Law enforcement especially values FinCEN's ability to use their artificial intelligence capability to 'mine' their data and to develop trends or areas that deserve a closer look. Agents from all the major law enforcement agencies sit at FinCEN and review these reports and law enforcement intelligence products." Digital Imaging Research Centre, Faculty of Computing, Information Systems and Mathematics, Kingston University. Be sure to see the Surveillance page. AITopics/LibrariesIn Search of Blessed Bots. By C. Brian Smith. Library Journal netConnect, Spring 2002 (April 15, 2002). "Call it the case of bots to the rescue. Despite their cute name, they could soon be a powerful addition to the librarians' and information professionals' toolkit. Eric Lease Morgan, head of the new Digital Access and Information Architecture Department at Notre Dame University Libraries and founder of Infomotions, Inc., defines a bot as 'a computer application mimicking or embodying elements of human intellect.' Also known as intelligent agents, bots are computer programs that act independently and autonomously -- but on behalf -- of another. They carry out all sorts of routine behind-the-scenes tasks, and their unflagging energy has played a part in the explosive growth of the Internet. They can perform such duties as information retrieval, meeting scheduling, and e-mail filtering. On a personal level, they can shop for books, movies, music, and more. ... With bots, librarians and information professionals are poised to step into the brave new world of artificial intelligence (AI). Though still largely in the experimental stages of use in libraries, bots promise time savings in our current work and the help needed to expand our roles. ... Two librarians at Robert Morris College, PA, are pioneers in applying bots to reference work. Systems librarian David Bennett and reference/bibliographic instruction librarian Jacqueline Corinth teamed up to implement a bot named Sylvie, who handled ready-reference and directional questions to free up staff for more challenging questions." Reading in the Age of Google - Contemplating the future with books that talk to one another. By Gregory Crane. Humanities Magazine (September / October 2005). "Twenty years ago, Marvin Minsky, a proponent of artificial intelligence, responded to this ancient challenge and imagined a time when people could not imagine a library in which the books did not talk to each other.The grand vision of artificial intelligence remains elusive, but simpler approaches have already allowed books to converse with one another and to adapt themselves to the needs of individual human readers. ... Personalization begins with systems trying to anticipate the readers' needs. At the Perseus Digital Library, machine learning and data mining also have been put to use to discover what questions people have previously asked when they encounter a text. By studying the queries people have made regarding a widely read passage by Ovid, we discovered that readers generally followed a small number of patterns. Once a reader asked about three or four words in a passage, we could predict most of the words about which they would ask next."
Project Aristotle(sm): "Automated Categorization of Web Resources, is a clearinghouse of projects, research, products and services that are investigating or which demonstrate the automated categorization, classification or organization of Web resources." Compiled and maintained by Gerry McKiernan, Science and Technology Librarian, Science and Technology Department, and Curator, CyberStacks(sm), Iowa State University. Digital Libraries and Autonomous Citation Indexing. By Steve Lawrence, C. Lee Giles, & Kurt Bollacker, NEC Research Institute. IEEE Computer, Volume 32, Number 6, pp. 67-71, 1999. "An ACI [Autonomous Citation Indexing] system can automatically create a citation index from literature in electronic format. Such a system can autonomously locate articles, extract citations, identify citations to the same article that occur in different formats, and identify the context of citations in the body of articles. The viability of ACI depends on the ability to perform these functions accurately. We built a prototype digital library called CiteSeer? that successfully performs these tasks with sufficient accuracy." Workshop on Artificial Intelligence for Cultural Heritage and Digital Libraries, AI*IA 2001 Conference - September 25-28 2001. Licklider, J.C.R. 1965. Libraries of the Future. The M.I.T. Press. AITopics/LogicPropositional, First-Order And Higher-Order Logics: Basic Definitions, Rules of Inference, and Examples. By Stuart C. Shapiro. In Lucja M. Iwanska & Stuart C. Shapiro, Eds., Natural Language Processing and Knowledge Representation: Language for Knowledge and Knowledge for Language, AAAI Press/The MIT Press, Menlo Park, CA, 2000, 379-395. Here are some excerpts:
Introduction to Logic. A tutorial from Dave Inman, School of Computing, South Bank University, London. Topics covered: What is Logic? Are we logical? An example of logic. What is good about logic? What is it used for? A little history. Simple types of logic. Complex types of logic. How do you represent the world in logic? How does Prolog work? Overview. References. Logic lecture slides and accompanying transcripts from Professors Tomás Lozano-Pérez & Leslie Kaelbling's Spring 2003 course, Artificial Intelligence. Available from MIT OpenCourseWare. AITopics/MachineTranslation
National Institute of Standards and Technology's 2005 Machine Translation Evaluation: "The objective of the MT evaluation series is to develop technologies that convert free text from a variety of languages into English.There were two source languages (Arabic & Chinese) and one target language (English) evaluated in the MT-05 evaluation."
Tongue twisters. Machine-translation systems chip away at language barriers. Richard A. Quinnell. CommVerge (August 2002). "Now, more than ever, communications and information exchanges are crossing both national and linguistic boundaries. Fortunately, the same computer systems that make such international connections possible can assist in breaking down the language barriers, via machine translation from one language to another. Unfortunately, they are far, far from perfect at doing so. But with careful utilization in appropriate applications, machine translation can open an inexpensive crack in linguistic barriers that would otherwise require costly human translation to scale. ... 'Machine translation is an artificial intelligence discipline, not simple pattern matching,' Akers says. 'It needs a deep understanding of grammar, semantics, and the like for the source language so it can do syntactic parsing.' It also needs an equal understanding of the target language's structure in order to synthesize its output sentences." ... and for a peek at the lighter side of Machine Translation see: Fun With Automatic Translation, from Shtick! / available from NewJersey.com / also available from The New York Times (August 16, 2002)
AITopics/Marketing
Sentimental Journey. New computer software applications -- in the labs and in the market -- are using emotion as data input and responding to it. "How does that make you feel?" asked the computer. By Esther Schindler. CIO (January 23, 2007). Lucrative answer to a million questions. By Peter Brown. The Times (May 24, 2003). "Five years ago Davin Yap, a Cambridge engineering researcher, was sharing a Darwin College bench with Dr David MacKay. They were beefing about their students. The undergrads had just discovered e-mail and were besieging the two academics with what are now known as Frequently Asked Questions. How much simpler if the FAQs could be answered automatically on a website. Maybe some artificial intelligence could be written that would recognise and learn from questions, while giving the correct answers? Lightbulbs flickered. 'I said, ‘I’ll do the plumbing, you do the smart stuff’,' Yap recalls. ... He and Mackay also had a company name -- Transversal -- and a professional product called Metafaq. The first customer after the launch in autumn 2001 was Procter & Gamble, for its recruitment website. Others since then have ranged from Sony’s PlayStation, Fujifilm and MFI to the DfES and JP Morgan." Capitalize on Customer Conversations with Speech Analytics. By Donna Fluss. Speech Technology Magazine (September / October 2005). "For years, speech analytics have been used worldwide by security organizations to help government agencies identify potential risks and threats. In the past two years, contact centers have begun to use speech analytics applications to capture and structure customer communications. The applications analyze the structured data to identify customer trends and insights for the purpose of improving service quality, customer satisfaction, and generating new revenue. There are three major analysis techniques and outputs from speech analytics: Keyword or Key Phrase Identification ... Emotion Detection ... Talk Analysis.... Today, more than 95 percent of the customer communications that flow through contact centers go to waste because enterprises do not have tools for capturing, analyzing and using this information." Spring comes to AI winter. By Heather Havenstein. Computerworld & IDG - Sweden (February 10, 2005)). "Researchers now are emerging from what has been called an 'AI winter' with renewed interest in the biology of the brain and research honed to practical applications in medicine, customer service, manufacturing, education and other areas. ... AI systems will handle tasks that humans aren't particularly good at today, like dependably answering tedious customer questions with an endless supply of patience. 'AI will mean ennoblement for the customer,' says [Robert] Hecht-Nielsen. 'Someone will answer calls in a call center and spend as much time as the customer needs, and they will be polite and fun. It just won't be a person.'" High-Tech Answers to Customers Queries. Web Technology Helps Consumers Find Own Solutions to Save Firms Time, Money. By Neil Irwin. The Washington Post (June 20, 2001). "The Ask George system is part of a quiet revolution in how companies and governments interact with consumers. The Internet is letting the public bypass phone representatives in many cases with do-it-yourself inquiries. The long-term result: lower spending on customer and constituent relations and cost savings that could be passed on to customers or taxpayers if the systems work correctly." Agent-Mediated Electronic Commerce. From Professor Nick Jennings, School of Electronics and Computer Science University of Southampton. "To achieve this degree of automation, and move to second generation e-commerce applications, a new model of software is needed. This model is based upon the notion of interacting agents (hence the term 'agent-mediated electronic commerce'). An agent is a software program that acts on behalf of its owner to achieve particular objectives. To do this, the software must exhibit the following properties: * it needs to be autonomous: capable of making decisions about what actions to take without constantly referring back to its user; * it needs to be reactive: able to respond appropriately to the prevailing circumstances in dynamic and unpredictable environments; * it needs to be proactive: able to act in anticipation of future goals so that its owner's objectives are met." Research: From lab to market. By Michael Kanellos. CNET News (June 16, 2004). "Data mining, the ability to find unexpected patterns in accumulated data, was born during a lunch break. At a customer conference in the early 1990s, an executive at British department store chain Marks & Spencer was explaining his database woes to Rakesh Agrawal, an information retrieval specialist at IBM. The store was collecting all sorts of data but didn't know what to do with it. So Agrawal and his team began devising algorithms for asking open-ended queries, eventually authoring a 1993 paper that would become required reading in data-mining science. The report has been cited in more than 650 other studies, making it one of the most widely cited papers of its kind. ... Agrawal, the data-mining pioneer, is today working on a system that will scramble customer data in a way that will allow companies to study buying trends or other patterns while preserving strict privacy." B-to-b sites get personal - Adapting the personalization technology consumer sites employ to encourage shoppers, businesses optimize user efficiency and convenience. By Judith Nemes, in the March 5, 2001 edition of "B to B". "'When someone is buying for a business function, they want to get to a Web site, fulfill their mission and get off the site,' Corvill said. 'In a business environment, it's less about enticement and more about convenience, efficiency and optimization.' ... Recommendation engines, one broad category, uses data-mining analytics, algorithms and other forms of artificial intelligence to analyze companies' or individuals' behavior patterns based on existing information from multiple data sources." Interview published Friday, March 9, 2001, in the San Jose Mercury News in which Walter Tackett, chairman, CEO and co-founder of NativeMinds, is asked: "Can you give me some idea what it takes to develop a specific character for a specific role on a corporate Web site?" His reply begins with: "A virtual representative is an employee of the company. So start with the job description...." International Workshop on Artificial Intelligence Applications to E-Commerce. June 25-28, 2001. Las Vegas, Nevada, USA. "E-commerce is growing at a staggering pace all over the world. Billions of dollars are being invested in E-commerce ventures. Efficient and convenient E-business systems are vital in improving business performance. Artificial Intelligence (AI) techniques are widely used in various industries. Now a days AI is also emerging in the E-commerce industry. AI is useful in searching the web, helping consumers in comparing various shops, automatically notifying customers with relevant events, and so on. Lot of research, development, and business is going on in this new multi-disciplinary filed." "See vReps in Action. Virtual representatives (vReps) are becoming more and more common on self-service sites. Verity Response lets you quickly deploy question and answer (Q & A) interfaces with images and personalities that match your brand." AITopics/MedicineRelational Agent Research being conducted by Timothy Bickmore, Assistant ProfessorCollege of Computer and Information ScienceNortheastern University. "I'm interested in the development and study of Relational Agents, which are computer agents designed to build and maintain long-term, social-emotional relationships with people. ... These agents are particularly effective for tasks in which long-term interactions and personal relationships are known to be important, such as in education, sales and marketing, and the helping professions. Of these, I have focused my recent work within the healthcare domain on health education and health behavior change applications." Be sure to see his Relational Agents page. Doctors' Orders - As expert systems become more expert, physicians see the advantages of taking on CPOE. By Mark Hagland. Healthcare Informatics (January 2003). "If the future is a clinically driven, elegantly managed, intelligent system--one that helps physicians optimize patient care and helps hospitals and medical groups constantly improve care delivery--then the folks at Ohio State University (OSU) Health System, Columbus, have at least glimpsed the future. They're in the vanguard of patient care organizations using computerized physician order entry (CPOE) systems which, authorities say, best represent the legacy of years of expert-systems development work in healthcare." Use of proteomic patterns in serum to identify ovarian cancer. By Emanuel F. Petricoin III, Ali M. Ardekani, Ben A. Hitt, et al. (2002). Lancet 2002; 359: 572-77.
Speech recognition technology finds a voice. Discussion at SCAR [Symposium for Computer Applications in Radiology] gets down to nuts, bolts, and templates in latest element of radiology's technology arsenal. By Merlina Trevino. SCAR Conference Reporter (2002). "It's been one of the most popular Diagnostic Imaging PACSpoll questions: Are you ready to replace traditional transcription services with speech recognition technology? More than 50% of the poll respondents answered with a resounding yes." Artificial Intelligence in Medicine. Published by Elsevier, this journal offers "original articles from a wide variety of interdisciplinary perspectives concerning the theory and practice of artificial intelligence (AI) in medicine, human biology, and health care."
"ISIS is a decision support system that helps physicians select the most cost-effective diagnostic imaging studies." Developed by the Division of Informatics, Department of Radiology, Medical College of Wisconsin The Third Workshop on Agents Applied in Health Care. 30 July 2005 Edinburgh, Scotland; held in conjunction with IJCAI2005. " AITopics/Military
Be sure to see their list of research projects. Tutoring for Future Combat. Embedded individual training on the way to deployment is fast becoming the wave of the future. By Patrick Chisholm. Military Training Technology. Volume 8, Issue 3 (September 08, 2003). "Conventional training methods present students with large amounts of information and test their recall, but do little to ensure that the student applies that knowledge correctly. The highly interactive learning environments of ITS [intelligent tutoring systems], by contrast, require students to apply their knowledge and skills. The ITS also answers user questions and provides individualized guidance. In the 1990s, the Air Force began using an ITS known as Sherlock for training on aircraft troubleshooting procedures. According to researchers at Stottler Henke Associates, a San Mateo, CA-based consulting firm specializing in ITS and artificial intelligence, students taught with Sherlock performed significantly better than the control group. After 20 hours of instruction, the students performed as well as technicians with four years of on-the-job experience." Fighting Talk. By Rob Coppinger. The Engineer (September 29, 2003). "DARPA will spend around $3bn (£1.8bn) this year on some 200 projects in computing, space weapons, counter-terrorism, unmanned aerial vehicles and biological defence. And that is only what it will openly admit to. The master of ceremonies at the Disneyland conference will be its director, Dr Anthony Tether. In a rare in-depth interview, the man at the heart of DARPA described how robotic armies are high on the agency's agenda." Agent Based Computing for Autonomous Intelligent Software. By James Hendler, Defense Advanced Research Projects Agency (DARPA) and Laura Douglass, Schafer Corporation. Software Tech News (October 2001; Volume 4, Number 4). "A key technological innovation capable of handling the complexity of modern warfare is that of software agents. Agent-based computing focuses on the development of distributed computational entities (software agents) which can act on behalf of, mediate or support the actions of human users and autonomously carry out tasks to achieve goals or assist the activities of the users in achieving those goals. In the military, using these agents will improve our information and decision management capabilities and thus drastically reduce the complexities of modern warfare." Spies in the Digital Age. By H. Keith Melton. From CNN's "Cold War" series. "The CIA and other intelligence services must operate with shrinking budgets and manpower -- the CIA will shrink 25 percent from its peak -- but confront an array of new threats to national interests in different parts of the globe. To meet these challenges, all intelligence services will be forced to rely on digital solutions, massive computers and artificial intelligence in linked computer networks and databases to compensate for the reduction of people and resources." Robotics to play major role in future warfighting. By JO1(SW) Ron Schafer. U.S. Joint Forces Command (July 29, 2003). "Project Alpha, a U.S. Joint Forces Command rapid idea analysis group, is in the midst of a study focusing on the concept of developing and employing robots that would be capable of replacing humans to perform many, if not most combat functions on the battlefield. The study, appropriately titled, 'Unmanned Effects: Taking the Human out of the Loop,' suggests that by as early as 2025, the presence of autonomous robots, networked and integrated, on the battlefield might not be the exception, but, in fact, the norm. ... The goal of the study, according to Gordon Johnson, the Unmanned Effects Team leader for Project Alpha, was to articulate a vision for the use of robotic forces and promote the formation of a Department of Defense-level office that will coordinate and integrate efforts across the armed services, ultimately resulting in joint-service development of unmanned effects (UFX), rather than the course of service-centric research that currently exists." Radar Project. Carnegie Mellon University School of Computer Science. "The overall goal is to develop a software-based 'cognitive personal assistant' that will help busy military commanders and managers to work more effectively, with less time wasted on routine tasks. This new technology should be equally valuable to managers in industry, academia, and government. Radar (short for for 'Reflective Agent with Distributed Adaptive Reasoning') will help its human master in many ways: scheduling meetings, allocating resources, maintaining a project web site, producing coherent reports from disorganized snippets of information, and helping the user to deal with the constant flood of E-mail. ... To accomplish all this, the Radar research team must employ techniques from a variety of fields, including machine learning, human-computer interaction, natural-language processing, optimization, knowledge representation, flexible planning, and behavioral studies of human managers." The U.S. Army AI Center became the Strategic and Advanced Computing Center (SACC) and is now the Chief Technology Office of the Chief Information Office (CIO.) AITopics/MoreGames"North Korea demonstrated its artificial intelligence technology when it won Japan's FOST, a tournament for computers playing Chinese chess, for two straight years in 1998 and 1999." - from North Korea suspected of training computer hackers. Associated Press / available from Hindustan Times (June 6, 2003) / also available from The Sydney Morning Herald (June 10, 2003).
AITopics/MusicThe Machine's Got Rhythm - Computers are learning to understand music and join the band. By Julie J. Rehmeyer. Science News Online (from Science News, Vol. 171, No. 16, April 21, 2007, p. 248). "Until recently, computers have had little insight into music. They've merely recorded it, stored it, and offered tools that people can use to produce or manipulate it. But now, researchers are teaching computers to recognize the basic musical elements: beat, rhythm, melody, harmony, tempo, and more. Computers with those skills are becoming musical collaborators. 'Technology is changing our sense of what music can be,' [Christopher] Raphael says. 'The effect is profound.' ... Raphael, an informatics researcher at the University of Indiana in Bloomington, compares the problem to speech recognition. 'There's been a veritable army of people who've worked on speech recognition for several decades, and [the problem] still remains open,' he says. 'Any time you deal with real data, there is a huge amount of variation that you have to understand.' ... Every year, various transcription programs go head-to-head in a competition called MIREX (Music Information Retrieval Exchange). The researchers set their programs loose on the same pieces of music and then compare results. This September, when the competition takes place in Vienna, it will for the first time include full transcriptions of polyphonic music, in which multiple notes are playing at the same time. ... Even as researchers continue to refine transcription methods, the work is spinning off remarkably useful tools. ... Some of the simplest are programs that display supertitles at the opera at just the right moment or that automatically turn the page for musicians. ... Score-alignment technology opened the door for Raphael to develop his computerized-accompaniment program. ... Raphael presented the system in Boston last July at a conference of the Association for the Advancement of Artificial Intelligence." Demonstration of Music Plus One - A Real-Time System for Automatic Orchestral Accompaniment. Christopher Raphael. 2006. In Proceedings of the Twenty-First National Conference on Artificial Intelligence, 1951 - 1952. Menlo Park, Calif.: AAAI Press."We demonstrate a system that creates a real-time accompaniment for a live musician performing a non-improvisatory piece of music. The system listens to the live player by performing a hidden Markov model analysis of the player's acoustic signal. A belief network uses this information, a musical score, and past rehearsals, to create a sequence of evolving predictions for future note-onsets in the soloist and accompaniment. These predictions are used to guide the time-stretched resynthesis of prerecorded orchestral audio using a phase vocoder."
The Robot Composer - Can computers write music? How would it make you feel if they can? Happy? Threatened? BBC Radio 3 Sunday Feature (August 31, 2003). "Chris Maslanka will be on a quest to discover just how good computers are getting at composing music. Computer programmes to write music have been around for nearly half a century, so by now they're getting pretty sophisticated. They use all sorts of techniques: ... programmes using the latest developments in artificial intelligence: neural networks and 'genetic algorithms' (inspired by the theory of evolution) ... Chris Maslanka meets the people whose computers are making the music, and leading thinkers in the field - including Pulitzer-prize-winning author Douglas Hofstadter and the 'father of artificial intelligence' Marvin Minsky." Links to the people and programs mentioned in the report are provided.
Robotic Percussionist: Researching to the Beat of a Different Drummer. Innovations @ Georgia Tech (March 30, 2006). "The robotic percussionist, developed by Director of Music Technology Gil Weinberg and graduate students Scott Driscoll and Travis Thatcher, is the result of research that crosses several disciplines and combines Weinberg's passions for music and technology to produce new and innovative music." Be sure to check out the videos, including: "The Computer Component of Haile." Voyager, a segment in the August 21, 2004 broadcast of Studio 360 titled: Robot, Fembot, Ribbon. From Public Radio International and WNYC New York Public Radio."The Voyager computer program is a powerful robot. It composes music--improvised, unpredictable music--using a virtual 64-piece orchestra. The Voyager’s inventor, George Lewis, improvises with his robotic partner, and creates music that we’d like to think only humans could make. Produced by Ted Panken." Experiments in Musical Intelligence. From Professor David Cope, University of California, Santa Cruz, Division of the Arts. "I began Experiments in Musical Intelligence in 1981 as the result of a composer's block. My initial idea involved creating a computer program which would have a sense of my overall musical style and the ability to track the ideas of a current work such that at any given point I could request a next note, next measure, next ten measures, and so on." Applications in Music. From Generation 5: Artificial Intelligence Repository. Music, Mind and Meaning. By Marvin Minsky.
Computer Music Journal (CMJ) is a quarterly Journal that covers a wide range of topics related to digital audio signal processing and electroacoustic music. It is published (in hard copy and on-line) by MIT Press." IJCAI. A collection of papers from The 14th International Joint Conference on AI (IJCAI-95) Workshop on Artificial Intelligence and Music which, according to the workshop summary, "were grouped around four major topics: Beat Induction and Structure Identification; Musical Learning; Music Analysis and Knowledge Representation; Composition and Improvisation." Computer Music Research Group. University of Huddersfield, UK. Using expertise from computer science and music, emphasis is on developing algorithms for sound synthesis, composition, computer assisted learning in music, and virtual instrument design. Scroll down the page and connect to CALMA: Computer Assisted Learning for Musical Awareness. International Computer Music Association - Resources: Their collection of links includes both academic and research institutions, publications, and many other destinations. AITopics/Namesakes
- from the Eliza entry in the Charles Babbage Institute's Software History Dictionary Project
You can also listen to it!
AITopics/NatureOfIntelligence
Expertise in Context: Human and Machine. Edited by Paul J. Feltovich, Kenneth M. Ford, and Robert R. Hoffman. AAAI Press. The following excerpt is from the Preface which is available online: "Several disciplines share an interest in understanding the concept of expertise. In particular, the nature of intelligence and expertise are matters of significant concern to psychologists, philosophers, and various kinds of cognitive scientists. Computerized 'expert systems' form the best known applications of artificial intelligence (AI). But what is the expertise that experts (human or otherwise) can be said to have? This issue raises many other questions, and has lately given rise to considerable controversy. Some of this discussion reaches to the very foundations of cognitive theory, with new perspectives contributed by the social sciences. ... How does 'expertise' differ from mere 'knowledge?' ... The nature of knowledge is central to AI. The large number of successful applications of conventional AI technology, utilizing knowledge obtained by careful conversations with human experts, has already begun to put a strain on the classical idea that knowledge can simply be written down (perhaps with a little effort and guided introspection)." Communication with Alien Intelligence. By Marvin Minsky (1985). "I'll propose two reasons why aliens will think like us, in spite of different origins. All problem-solvers, intelligent or not, are subject to the same ultimate constraints - limitations on space, time, and materials. In order for animals to evolve powerful ways to deal with such constraints, they must have ways to represent the situations they face, and they must have processes for manipulating those representations." Intelligence as a Resource. Chapter 3 of Increasing Your Expertise as a Problem Solver: Some Roles of Computers. By Dr. "Dave" Moursund (1996; revisions and updates added in Fall, 2001). "This chapter gives a definition of intelligence and then explores a variety of intelligences that people have." Mind of the company - Science is finding that mimicking living systems to produce robots is about understanding biology, not physics. There are lessons here for the way we run our corporations. By Tim Wallace. Financial Review Boss (March 14, 2003). "[Rodney] Brook's work on AI challenges us to rethink OI (organisational intelligence) and to smash the machine, rebuilding it from the bottom up - fast, cheap and out of control. ... The most celebrated of all early efforts to create a robot that could do childish things resulted in Shakey, built at the Stanford Research Institute in the late 1960s to early 1970s, and so named because of the way its camera and TV transmitter mast shook when it moved. ... The designers of Shakey, and of the projects following it, believed that for a robot to act intelligently in the world it first needed an accurate model of that world. ... What must be happening in insects, Brooks realised, was sensing connected to action - sensors to actuators - very quickly. The key to building a similarly efficient robot, he concluded, was to have it react to its sensors in the same way, so it did not need a detailed computational model of the world. 'If the building and maintaining of the internal world model was hard and a computational drain, then get rid of the internal model. Every other robot had had one. But it was not clear that insects had them, so why did our robots necessarily need them?'" Hauser, Marc D. 2000. Wild Minds - What Animals Really Think. New York: Henry Holt and Company, Inc. AITopics/Networks
SpyForce-AI protects against insider threats - Software uses artificial intelligence to detect anomalous behavior on networked systems. By Earl Greer. FCW.com News (November 12, 2006). "Information technology security managers are growing increasingly concerned about insider threats, which occur when employees compromise sensitive information stored on networked systems.With that in mind, we decided to test Nowell’s SpyForce-AI, which uses artificial intelligence to monitor network use, to see if it could give us peace of mind." The search for intelligence- Smart routers from promising startups could make the Internet faster and more reliable. Their biggest challenge: timing. By Om Malik. Red Herring (February 7, 2002). "Enter the intelligent-routing companies. If the technology works as promised, equipment being developed by these companies will have the ability to 'look' into a network and quickly gauge performance. If there is congestion on a particular network route, then the intelligent router instructs data traffic to take an alternate, faster route. This equipment can also instruct the traffic--depending on the urgency of the data being transmitted--to use networks from a carrier that provides lower-cost service at certain times of the day." CERIAS. "The Center for Education and Research in Information Assurance and Security, or CERIAS, is the world's foremost University center for multidisciplinary research and education in areas of information security. Our areas of research include computer, network, and communications security as well as information assurance. We hope you'll find this site and the archive useful." Jeremy Frank's Introduction to Intrusion Detection. "Intrusion Detection is the identification of attempted or ongoing attacks on a computer system or network. Issues in ID research include data collection, data reduction, behavior classification, reporting and response. Although there are many significant open problems in ID research, my work has focused on data reduction and classification. Data reduction consists of analyzing a collection of data in order to identify the most important components of the data, thereby reducing processing time, communications overhead and storage requirements. Classification is the process of identifying attackers and intruders. Artificial intelligence techniques have been used in many IDSs to perform these important tasks." or have the option of various formats if you get it from ResearchIndex Also available in other formats from ResearchIndex.
AITopics/NeuralNetworksComputers and Symbols versus Nets and Neurons, Chapter One of Neural Net notes, by Kevin Gurney, Psychology Department, University of Sheffield. Connectionism. James W. Garson authored this entry in the Stanford Encyclopedia of Philosophy. Topics include: A Description of Neural Networks, Neural Network Learning and Backpropagation, and Connectionist Representation. Their coverage of Neural Networks begins with Slide 12.2.1 in Chapter 12, Machine Learning IV, and continues with a discussion of training neural nets in Chapter 13, Machine Learning V. Neural nets explained: How neural networks give machines the ability to learn from experience. By Alan Zeichick From the August 2000 issue of Red Herring Magazine. Web Applets for Interactive Tutorials on Artificial Neural Learning. By Fred Corbett. "This tutorial was developed as part of my undergraduate thesis in Computer Engineering at the University of Manitoba, and was supervised by Dr. H. C. Card. The goal of this project was to demonstrate some elementary aspects of artificial neural networks (ANNs) in an interactive and, hopefully, interesting manner. ... This tutorial is currently divided into three sections [Artificial Neuron, Perceptron Learning, and Multi-Layer Perceptron]. Each section deals with a specific aspect of neural networks and includes a JavaTM applet. The sections include a brief introduction, some theory behind the applet, a set of instructions for using the applet, the source code, and the applet itself." AITopics/NeuroScienceComputers That Think, Really - Cognitive Computing could revolutionize life, but there's no telling when. By E. Cubarrubia. Red Herring (August 7, 2006 issue date). "Cognitive computing technology exists today, albeit in an early-stage form, and its supporters hope to turn it into a profitable business. The technology promises to go further than traditional 'artificial intelligence,' or AI. In cognitive computing, machines have the ability to learn like humans do and respond to unexpected events, rather than simply calling upon existing knowledge or using logical courses pre-programmed into software like their AI precursors. That means cognitive devices can develop reasoning abilities, which proponents say will eventually blossom into intelligence and consciousness -- just like a human brain. The ultimate cognitive machines that some neurologists and computer scientists envision don’t yet exist, of course, but several companies are making forays into that space." AITopics/NaturalLanguageUnderstandingNarrative Prose Generation. By Charles Callaway and James Lester. In Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, Seattle, WA, August 2001. Natural Language Understanding Lecture Notes from Professors Tomás Lozano-Pérez & Leslie Kaelbling's Spring 2003 course: Artificial Intelligence. Available from MIT OpenCourseWare.
Special Interest Group on Text Generation (SIGGEN), Association for Computational Linguistics. Lots of information, plus links to research groups, bibliographies, and more. House, David. Interactive Text Summarization for Fast Answers. The MITRE Advanced Technology Newsletter (July 1997). "By interactively selecting terms of interest and viewing the corresponding context-dependent summaries, users can quickly find answers relevant to their queries. The technology behind WebSumm exploits recent advances in artificial intelligence and information retrieval." AITopics/NonmonotonicityNon-monotonic Logic. From Anthony Aaby, Walla Walla College Computer Science Department. Here's a good opportunity to see the language of logic.
From Building Intelligent Legal Information Systems: Representation and Reasoning in Law. Introduction to Artificial Intelligence LECTURE 11: Nonmonotonic Reasoning. (29 slides.) From the School of Computer Science and Engineering at The Hebrew University of Jerusalem. "The International Workshops on Nonmonotonic Reasoning (NM) aim to bring together active researchers interested in the area of nonmonotonic reasoning to discuss current research, results, and problems of both a theoretical and practical nature. The field of nonmonotonic reasoning includes work on circumscription, autoepistemic and default logic, truth maintenance, closed-world databases, logic programming, probabilistic reasoning, and related systems. The theory of nonmonotonic reasoning has helped provide a clear and formal framework that can be used to understand and compare issues in action representation, planning, and other areas." AITopics/OntologiesThe State of the Art in Ontology Design: A Survey and Comparative Review. By Natalya Fridman Noy and Carole D. Hafner. AI Magazine, 18(3): 53-74 (Fall 1997). This paper is based on the authors' presentation at the Twelfth Innovative Applications of Artificial Intelligence Conference (IAAI-2000). "Our study shows there is great diversity in the way ontologies are designed and the way they represent the world. By identifying the similarities and differences among existing ontologies, we clarify the range of alternatives in creating a standard framework for ontology design."
AITopics/OthelloThe inner workings of strong Othello programs, by Gunnar Andersson. Topics covered include searching, position evaluation, and opening knowledge. Also see Zebra, an Othello program he co-developed. Other resources available at this site include the essay, The inner workings of strong Othello programs. Desdemona: Interactive Othello for the Web. By Dominic Mazzoni, Harvey Mudd College, Claremont California. Hannibal. "Hannibal uses a fixed depth alpha-beta search with iterative deepening. The search tree is remembered from one iteration to the other to speed up computations. The evaluation function is evaluated at the leaves of the tree." Zebra is an Othello progarm developed by Gunnar Andersson and Lars Ivansson. AITopics/PatternRecognitionThe Robot Shopkeeper - New customer behavior technology from NCorp gives a personal touch to online shopping. By Thomas K. Grose. TIME Europe: Digital Europe Start-Up of the Week (September 2, 2002). "In today's world of online shopping, call centers and impersonal supermarkets, that human touch is missing. But technology developed by a former Cambridge University researcher could help introduce old fashioned personal care into online shopping. Mike Lynch, who has a doctorate in pattern recognition, began developing algorithms to help identify patterns more than a decade ago. ... The basic technology is a form of Artificial Intelligence that 'gives computers the ability to recognize patterns the way humans can,' explains Nick Bidmead, NCorp chief executive." AITopics/PetroleumIndustry
Artificial Intelligence Expands Frontiers in Asset Management - Condition Monitoring and Predictive Maintenance Systems Make AI Pay Off With Lower Maintenance Costs, Improved Forecasting, and Fewer Unplanned Shutdowns. By Bob Waterbury. Control Magazine (November 16, 2000). "Why Artificial Intelligence? Methods, targets, and equipment settings for normal steady-state operations are well understood. Most plants have software and instrumentation that handle this quite nicely. Outside of normal operating conditions, however, control system efficiency may deteriorate rapidly as alarms seem to cascade into uncontrollable system breakdown. Sometimes algorithms and equation-based software solutions can handle these abnormal situations. But as systems become more complex and interconnected, artificial intelligence techniques are used increasingly to predict failures before they occur, and to deal with process upsets before human and financial costs spiral out of control. ... Artificial intelligence techniques have been quietly embedded into plant solutions throughout the process industries. Often, we are simply unaware of their presence or their function unless specifically pointed out." REACT: The Reservoir Evaluation and Advanced Computational Technologies Research Group at The Petroleum Recovery Research Center (PRRC) of New Mexico Tech. Projects include FEE Tool: The Fuzzy Expert Exploration Tool project. (Also see: $2.6 Million Grant to PRRC for "Fuzzy Expert" System.) Petroleum Offshore Platform Startup Via an Intelligent System: Integrated Expert System and Fuzzy Controller Applied to Startup Process. By Mario Cesar M. Campos, Eduardo Satuf, and Marcello de Mesquita. PC AI (Volume 17, Number 2; pages 24 - 31). "The intelligent system uses numerous heuristic rules to automate the startup procedures, such as opening valves while simultaneously monitoring the process variables. A fuzzy controller optimizes the opening of the oil wells, minimizing the startup time. The implementation of this intelligent system is for the Petrobras, a Brazilian oil company, P-19 platform in Campos Basin Brazil. The prototype has been operating since October 1998." AITopics/PlanningPlanning and Scheduling. A very clear presentation from NASA offered as part of its site about Deep Space 1's Remote Agent.
Planning and Scheduling. In CRC Handbook of Computer Science and Engineering. (1996) By Thomas Dean and Subbarao Kambhampati. "In this chapter, we use the generic term planning to encompass both planning and scheduling problems, and the terms planner or planning system to refer to software for planning or scheduling. Planning is concerned with reasoning about the consequences of acting in order to choose from among a set of possible courses of action. In the simplest case, a planner might enumerate a set of possible courses of action, consider their consequences in turn, and choose one particular course of action that satisfies a given set of requirements. ... To distinguish between planning and scheduling we note that scheduling is primarily concerned with figuring out when to carry out actions while planning is concerned with what actions need to be carried out. In practice this distinction often blurs and many real-world problems involve figuring out both what and when." (Postscript version available from the Brown University Artificial Intelligence Group collection of publications.) Planning and Scheduling Publications. From the University of Salford. An extensive collection of papers available online. AITopics/PokerBots now battle humans for poker supremacy. By Shawn P. Roarke. FOXSports.com (July 19, 2005). "That threat is the poker bot, a computer program designed to play nearly statistically flawless poker. 'There are a lot of people out there that have seen the opportunity to make money out there and have built online poker bots and are being deceitful,' says Dr. Jonathan Schaeffer, a professor of computer science at the University of Alberta. And, Schaeffer should know. He has worked extensively in the past 14 years to develop just such a poker bot. However, unlike the opportunists out there, Schaeffer's work has been above-board and out in the open. As the leader of The University of Alberta's Computer Poker Research Group, Schaeffer has helped develop two poker bots, dubbed 'Vex Bot' and 'Spar Bot.' Capable of playing poker at a very high level, but only in head-to-head scenarios, the bots are used by researchers to test the limits of artificial intelligence. ... The rapid evolution of these poker bots was on display last week at Binion's Casino in Las Vegas, where the first organized public competition between poker programs was held. Referred to as the World Poker Robot Championships, this competition pitted six poker programs against each other, playing limit hold 'em for a $100,000 prize -- put up by Golden Palace. In the end, 'Poker ProBot,' engineered by 37-year-old Hilton Givens of Lafayette Ind., emerged as the victor after five rounds and nearly my 5,000 hands. ... Not only did Givens earn a cool $100,000, he got the opportunity to have his program match wits with Laak, one of the game's most accomplished professionals. ... Laak won the showdown in 399 hands. Laak also defeated the University of Alberta's Poki X...." AITopics/PoliticsAndForeignRelationsFree translation software unveils Arab views. The Associated Press / available from CNN.com (December 31, 2001). "In October, Cairo-based Sakhr Software released its Arabic-to-English translation software -- free for the world to use -- on the company's Arabic language Web portal at Ajeeb.com. ... 'It's the beginning of a solution to this misunderstanding problem,' said Fahad Al-Sharekh, chief executive of Ajeeb.com. 'This is what's going to bridge the gap between the two civilizations.'" Investigation of the Potential Contribution of AI-Methods to the Avoidance of Crises and Wars. Austrian Research Institute for Artificial Intelligence. Read about their results, and see their list of publications and collections of related links. Thinking About Foreign Policy: Finding an Appropriate Role for Artificially Intelligent Computer. By John C. Mallery. "This paper was presented to the panel on ``Analytical Frameworks for the Analysis of Conflict,'' at The 1988 Annual Meeting of the International Studies Association, Adam's Mark Hotel, St. Louis, Missouri, March 28 to April 3, 1988. An earlier version was submitted as a Master's Thesis to the M.I.T. Department of Political Science, February, 1988."
AITopics/PublicHealthAndWelfareExperts call for active surveillance of drug safety - Drug agency urged to use latest technology to spot side effects early. By Meredith Wadman. Nature 446, 358-359 (March 22, 2007; subscription req'd). "Last week, Mark McClellan, a former FDA commissioner, told a Senate committee considering new drug-safety legislation that the system 'needs to do better than just seeing the tip of the iceberg of a safety problem after it has already hit us'. Health-information technology for drug safety is 'an idea whose time has come', he added. McClellan and others are pushing the idea of data mining of existing health-record databases as an active surveillance system to pick up early warnings of adverse side effects. ... The same thinking is gaining currency in Europe."
Hospitals prepare for attack with tracking, upgrades. By Meredith Narcum. The Gazette (September 27, 2002). "As the nation prepares smallpox vaccination plans, area hospitals are working on a way to detect a bioterrorist attack quickly. County hospitals gained access this month to a computerized disease-surveillance system that will help doctors and county officials identify unusual trends in patients' symptoms. Hospital staff members enter symptoms into the system, which then tracks any abnormal patterns. The system also tracks school absentee rates and drug purchases at major pharmacy chains such as CVS, said Kathy Hurt-Mullen, one of two county epidemiologists. ... Montgomery County is the first county to use the system, which Johns Hopkins Laboratory of Applied Physics began developing in 1998, Hopkins program manager Joe Lombardo said."
Balancing Data Needs And Privacy. Opinion by Leslie Walker. The Washington Post(May 8, 2003). "[Teresa] Lunt's project intrigues me. It falls into a relatively young field of computer science dubbed 'data privacy,' in which researchers are exploring ways to scrub databases of personally identifiable information without trashing the usefulness of the digital repositories for socially valuable research. 'It is an emerging and important field,' said Latanya Sweeney, the computer scientist who directs Carnegie Mellon University's Laboratory for International Data Privacy. Sweeney's team recently did data-privacy development work for the federal government that is just starting to be used in the Washington region for early detection of bioterrorist attacks, through screening such records as emergency-room visits. 'It allows the sharing of information for bioterrorism surveillance with guarantees that no one can be identified,' Sweeney said." Global Public Health Intelligence Network (GPHIN), managed by the Centre for Emergency Preparedness and Response (CEPR) at the Public Health Agency of Canada. "GPHIN is a secure, Internet-based 'early warning' system that gathers preliminary reports of public health significance in seven languages on a real-time, 24/7 basis. This unique, multilingual system gathers and disseminates relevant information on disease outbreaks and other public health events by monitoring global media sources such as news wires and web sites."
AITopics/QualitativeReasoningQualitative Reasoning Tutorial and Qualitative Reasoning FAQs. From MONET (MONET is a Network of Industrialists, Academics and Researchers with a common long-term technological development objective in Model Based Systems & Qualitative Reasoning.) Smart Tools Lab at CMU. The Approximate and Qualitative Reasoning (AQR) Group is part of the Institute for Representation and Reasoning within the Division of Informatics at the University of Edinburgh. MONET is a Network of Industrialists, Academics and Researchers with a common long-term technological development objective in Model Based Systems & Qualitative Reasoning (MBS & QR). The Qualitative Reasoning Community. "The purpose of this Web page is to provide archival information such as conference/workshop information, bibliography, or discussion through the mailing list." Qualitative Decision Theory. "This site collects information relating to Qualitative Decision Theory, including information about the March, 1997 AAAI Symposium on Qualitative Preferences in Deliberation and Practical Reasoning." AITopics/RealTimeReasoningAnytime Algorithms. By Tadeusz P. Dobrowiecki, Budapest University of Technology and Economics, Department of Measurement and Information Systems. "The term "anytime algorithm" is currently used to refer to algorithms that provide approximate answers to difficult problems in such a way that, minimally: (1) An answer is available at any point in the execution of the algorithm, (2) The quality of the answer improves with an increase in execution time."
"CIRCA combines artificial intelligence and real-time systems technologies to achieve intelligent hard real-time control of domains such as robots, manufacturing/assembly, and aviation. The University of Michigan based CIRCA research is conducted jointly between the Artificial Intelligence Laboratory and the Real Time Computing Laboratory. "
A Survey of Research in Deliberative Real-Time Artificial Intelligence. By Alan Garvey and Victor Lesser. Real-Time Systems, Volume 6, Number 2: 317-347 (January 1994). "This paper surveys recent research in deliberative real-time artificial intelligence (AI). Major areas of study have been anytime algorithms, approximate processing, and large system architectures." Real-Time Knowledge-Based Systems. by Thomas J. Laffey, Preston A. Cox, James L. Schmidt, Simon M. Kao, Jackson Y. Read. AI Magazine 9(1): 27-45 (Spring 1988). "Real-time domains present a new and challenging environment for the application of knowledge-based problem-solving techniques. However, a substantial amount of research is still needed to solve many difficult problems before real-time expert systems can enhance current monitoring and control systems. In this article, we examine how the real-time problem domain is significantly different from those domains which have traditionally been solved by expert systems. We conduct a survey on the current state of the art in applying knowledge-based systems to real-time problems and describe the key issues that are pertinent in a real-time domain. The survey is divided into three areas: applications, tools, and theoretic issues. From the results of the survey, we identify a set of real-time research issues that have yet to be solved and point out limitations of current tools for real-time problems. Finally, we propose a set of requirements that a real-time knowledge-based system must satisfy." AITopics/ReinforcementLearningReinforcement Learning: A Survey. By Leslie Pack Kaelbling, Michael L. Littman, and Andrew W. Moore. Journal of Artificial Intelligence Research (1996), 4:237--285. "This paper surveys the field of reinforcement learning from a computer-science perspective. It is written to be accessible to researchers familiar with machine learning. Both the historical basis of the field and a broad selection of current work are summarized. Reinforcement learning is the problem faced by an agent that learns behavior through trial-and-error interactions with a dynamic environment." AITopics/ScientificDiscovery2020 Computing: Exceeding human limits. Scientists are turning to automated processes and technologies in a bid to cope with ever higher volumes of data. But automation offers so much more to the future of science than just data handling. By Stephen H. Muggleton. Nature 440, 409-410 (23 March 2006). "During the twenty-first century, it is clear that computers will continue to play an increasingly central role in supporting the testing, and even formulation, of scientific hypotheses. This traditionally human activity has already become unsustainable in many sciences without the aid of computers. This is not only because of the scale of the data involved but also because scientists are unable to conceptualize the breadth and depth of the relationships between relevant databases without computational support. The potential benefits to science of such computerization are high -- knowledge derived from large-scale scientific data could well pave the way to new technologies, ranging from personalized medicines to methods for dealing with and avoiding climate change. [fn: Towards 2020 Science (Microsoft, 2006)]. ... Meanwhile, machine-learning techniques from computer science (including neural nets and genetic algorithms) are being used to automate the generation of scientific hypotheses from data. Some of the more advanced forms of machine learning enable new hypotheses, in the form of logical rules and principles, to be extracted relative to predefined background knowledge. ... One exciting development that we might expect in the next ten years is the construction of the first microfluidic robot scientist, which would combine active learning and autonomous experimentation with microfluidic technology." Introducing robo-scientist - Could robots take over from graduate students in the lab? By Mark Peplow. Nature (January 15, 2004). "A robot scientist has been unveiled that can formulate theories, carry out experiments and interpret results - all more cheaply than its human counterparts. As far as artificial intelligence goes, the Robot Scientist - designed by Ross King of the University of Wales in Aberystwyth, UK, and his colleagues - isn't as smart as other computers, such as those that compete in international chess competitions. But combining the smarts of a computer with the agility of a robot wasn't trivial. ... Geneticist Stephen Oliver of the University of Manchester, UK, who helped to select the robot's research project, says there is potential for the robot to more than just drudgery. 'The next big step is to make our robot discover something completely new,' says Oliver, 'perhaps by applying it to drug discovery.'"
Editorial: Scientific Discovery and Simplicity of Method. By Herbert A. Simon, Raul E. Valdes-Perez and Derek H. Sleeman. (1997). Artificial Intelligence, 91(2):177-181. ""[C]omplexity of programs or of their outputs is not a measure of their 'intelligence'. Given very complex tasks, complex algorithms may be a necessity, but they are clearly not a virtue. A critical lesson of artificial intelligence, and of computing in general, is that if a task domain has strong structure and if sufficient domain information can be obtained, either a priori or in the course of computation, then rather simple programs may suffice." Text-Based Discovery in Biomedicine: The Architecture of the DAD-system. By M. Weeber, H. Klein, A. R. Aronson, J. G. Mork, L. Jong-van den Berg, and R. Vos. Presented at The American Medical Informatics Association 2000 Symposium. "Current scientific research takes place in highly specialized contexts with poor communication between disciplines as a likely consequence. Knowledge from one discipline may be useful for the other without researchers knowing it. As scientific publications are a condensation of this knowledge, literature-based discovery tools may help the individual scientist to explore new useful domains. We report on the development of the DAD-system, a concept-based Natural Language Processing system for PubMed citations that provides the biomedical researcher such a tool." AITopics/ScrabbleComputer Playing of Scrabble. By Kenneth Tam. 1998. A detailed description of a senior undergraduate computer science programming project at the University of Waterloo, Ontario, Canada. AITopics/SearchSearch lecture slides and accompanying transcripts from Professors Tomás Lozano-Pérez & Leslie Kaelbling's Spring 2003 course, Artificial Intelligence. Available from MIT OpenCourseWare. "Search plays a key role in many parts of AI. These algorithms provide the conceptual backbone of almost every approach to the systematic exploration of alternatives."
Laboratory Resources on Search and Game Playing. From the 1994 workshop, "Providing and Integrating Educational Resources for Faculty Teaching Artificial Intelligence. LISP program code is offered for A-Star algorithm, the 8-puzzle, Depth-First Search, and many more search methods. AITopics/SmartHousesFujitec eases bottlenecks. By Anna Guido. The Cincinnati Enquirer (January 16, 2006). "A new elevator system developed by Fujitec America Inc. alleviates passenger bottlenecks in lobbies and in other high-traffic areas. The Destination Floor Guidance System - which was put into operation Friday in the Metropolitan Park West Tower in downtown Seattle - minimizes stops by grouping together passengers with common destinations. ... The Neuros Logic program that runs the system rationalizes and manages the elevator traffic patterns as they change throughout the day using technology such as artificial intelligence, fuzzy logic and genetic algorithms. ... Fujitec says only its system incorporates artificial intelligence to learn the building's traffic flow." Blobs, Pods and People. By Linda Hales. The Washington Post (March 25, 2001). "[T]hanks to computer-aided design and a host of information age innovations, far-out fantasy houses are coming closer to reality. .... Add the potential of artificial intelligence, biometric sensing, robotics and mass customization, and it's little wonder that designers are imagining a new generation of houses in which people rule their environment, rather than submit to them. ... [Kent] Larson envisions a house so wise and helpful that it would know whether an elderly resident living alone was staying in bed too long, or walking differently ...." What is Ambient Intelligence? ... '[O]ur vision of 'Ambient Intelligence': people living easily in digital environments in which the electronics are sensitive to people's needs, personalized to their requirements, anticipatory of their behaviour and responsive to their presence."
Inspire - Infotainment managment with speech interaction via remote-microphones and telephone interfaces. Knowledge S.A.. consortium co-ordinator. "The ever-increasing complexity of home appliances and services, combined with the difficulties encountered by a great portion of the population to handle complex equipment or the inability of elderly and disabled people to use them, renders the creation of intelligent, intuitive and flexible interfaces, facilitating human-machine interaction, an endeavour of paramount importance. This can be achieved by e.g. the integration of leading edge speech technologies. Emerging voice-controlled consumer electronics will be introduced in the near future as standalone devices. With INSPIRE we aim at the integration of a multilingual, interactive, natural, speech dialogue-based assistant for wireless command and control of home appliances (e.g. consumer electronics)." "The MavHome Smart Home project is a multi-disciplinary research project at the University of Texas at Arlington focused on the creation of an intelligent home environment. Our approach is to view the smart home as an intelligent agent that perceives its environment through the use of sensors, and can act upon the environment through the use of actuators. The home has certain overall goals, such as minimizing the cost of maintaining the home and maximizing the comfort of its inhabitants. In order to meet these goals, the house must be able to reason about and adapt to provided information." Room of the Future at Accenture Technology Labs "demonstrate[s] how existing technology can provide practical solutions to some of the issues facing our growing aging population. Prototypes we have developed include:Activity Monitoring: Uses sensors and video cameras to track the movements of a typical home user alongside artificial intelligence to interpret and act on situations that occur, as well as create insight into long-term behavioural variations.Caring Plant: A ‘smart’ plant equipped with motion sensors and the ability to communicate, collect, store and analyze information. ..." Pentland, Alex P. Smart Rooms. Scientific American. April 1996. "In creating computer systems that can identify people and interpret their actions, researchers have come one step closer to building helpful home and work environments." AITopics/SocialScience
Mind-Expanding Machines - Artificial intelligence meets good old-fashioned human thought. By Bruce Bower. Science News Online (Week of August 30, 2003; Vol. 164, No. 9). "In the workplace, computers are virtuosos of information storage. However, a computer system known as Brahms sings a different tune. It discerns revealing patterns in people's work behaviors and simulates ways to get their jobs done more effectively. ... The system builds on social science theories that regard each person's behaviors as being structured by broad pursuits, which researchers often call activities. In an office, common activities include coffee meetings with a supervisor, reading mail, taking a break, and answering phone messages. Activities provide a forum for addressing specific job tasks. A morning coffee meeting, for example, may determine who will make an important sales call later in the day. Brahms creates a computerized cartoon of how a work group's members perform their activities and tasks. The system's software is based on simulations of interactions among virtual individuals." Who Loves Ya, Baby? Pass your e-mail through some new software and the answer will become obvious. By Steven Johnson. Discover (April 2003; Vol. 24 No. 4). "In his classic novel Cat's Cradle, Kurt Vonnegut explains how the world is divided into two types of social organizations: the karass and the granfalloon. ... For most of the past 50 years, computers have been on the side of the granfalloons, good at maintaining bureaucratic structures and blind to more nuanced social interactions. But a new kind of software called social-network mapping promises to change all that. ... Mapping social networks turns out to be one of those computational problems -- like factoring pi out to a hundred decimal points or rendering complex light patterns on a 3-D shape -- that computers can do effortlessly if you give them the right data. Until software designer Valdis Krebs came along, however, there wasn't an easy way to translate social interactions into a machine-readable language.... Social mapping is not just for corporate sociologists. Krebs has used his software to analyze the social networks visible in book-buying patterns on Amazon.com, by tracking the 'people who bought this book bought these other books' feature. ... Not surprisingly, social-network software is ripe for political analysis." I, Decision Science, and Psychological Theory in Decisions about People: A Case Study in Jury Selection. By Roy Lachman (1998). AI Magazine, 19(1): 111-129. "AI theory and its technology is rarely consulted in attempted resolutions of social problems. Solutions often require that decision-analytic techniques be combined with expert systems. The emerging literature on combined systems is directed at domains where the prediction of human behavior is not required. A foundational shift in AI presuppositions to intelligent agents working in collaboration provides an opportunity to explore efforts to improve the performance of social institutions that depend on accurate prediction of human behavior. ... The system presented demonstrates the challenges and opportunities inherent in developing and using AI-collaborative technology to solve social problems." Dynamics of Multiagent Systems. From the Xerox Palo Alto Research Center. "Multiagent systems arise in human societies, biological ecosystems, the immune system and distributed computation. While very different in detail they all face the issue of producing complex global behavior through the local interactions of their constituent parts. This is particularly problematic since the individual parts have only a limited view of the system as a whole." Topics include Dynamics of Cooperation in Societies, Computational Societies and Economies, and Agent-Based Control of Smart Matter, and they offer lots of papers for those who want to explore these areas in depth. "Social Science Computer Review is an interdisciplinary journal covering social science instructional and research applications of computing, as well as societal impacts of information technology. Topics include: áartificial intelligence...." International Network for Social Network Analysis (INSNA) The Semantic Web. A new form of Web content that is meaningful to computers will unleash a revolution of new possibilities. By Tim Berners-Less, James Hendler, and Ora Lassila. Scientific American (May 2001). "Human endeavor is caught in an eternal tension between the effectiveness of small groups acting independently and the need to mesh with the wider community. A small group can innovate rapidly and efficiently, but this produces a subculture whose concepts are not understood by others. Coordinating actions across a large group, however, is painfully slow and takes an enormous amount of communication. The world works across the spectrum between these extremes, with a tendency to start small - from the personal idea - and move toward a wider understanding over time. An essential process is the joining together of subcultures when a wider common language is needed." AITopics/Software
"AI packages and toolboxes that are availbale for free and which may be used for non-commercial development." A collection from the students in the Intelligent Systems Program at the University of Pittsburgh. Machine Learning network Online Information Service's (MLnet OiS) software collection. CLIPS: A Tool for Building Expert Systems. Maintained by Gary Riley. eSTAR: "The eScience Telescopes for Astronomical Research (eSTAR) Project is a robotic telescope network. At one end of the system is an Intelligent Agent (IA). This is a piece of software that resides on a user's local machine. It can request observations from telescopes on the network. It will recieve the results of these observations which it can analyse and potentially follow up interesting observations. The IA was written for the prototype in Perl, and several middleware modules which have been developed for this task are being released by the project under the GNU Public License." ID3 algorithm. Public domain implementation available from MLnet. "The algorithm ID3 (Quinlan) uses the method top-down induction of decision trees." Neural Nets Research Group Software [they are part of the Artificial Intelligence Lab and the Computer Science Department at the University of Texas at Austin] for Natural Language Processing, Self-Organization, and Neuro-Evolution. SBook®5. Developed by Simson L. Garfinkel. "SBook5 is now an abandoned project. The complete source code, including the AI engine, is now being made available to the community. ... SBook®5 is an extremely fast, AI-based personal information manager." (For some background, see: Giving Up on SBook - After 16 years, I’ve given up on my favorite application. By Simson Garfinkel. Technology Review Editors' Blog. January 16, 2007.)
Simulators of Historic Machines. "This archive contains software to simulate the behaviour of historic computers." Provided by the Computer Conservation Society. Speech Software & Hardware from the comp.speech Frequently Asked Questions WWW site: audio hardware, speech synthesis systems, signal processing, handicap aids, and more. "Transcriber is a tool for assisting the manual annotation of speech signals. It provides a user-friendly graphical user interface for segmenting long duration speech recordings, transcribing them, and labeling speech turns, topic changes and acoustic conditions. It is more specifically designed for the annotation of broadcast news recordings, for creating corpora used in the development of automatic broadcast news transcription systems, but its features might be found useful in other areas of speech research. ...Transcriber is distributed as free software under GNU General Public License." Authored by Claude Barras, CNRS/LIMSI, and coordinated by Edouard Geoffrois, DGA/DCE/CTA/GIP. MajorSpot community - "a site dedicated to making artificial intelligence a reality for programmers around the globe. This community is proud to be the home of the MajorSpot AI SDK, an open-source Java software component aimed at helping software developers design their own AI-driven software using genetic algorithms, neural networks, fuzzy logic, wavelet analysis and other tools."
Openness makes software better sooner - Sharing code for computer software is best way to rid it of bugs. By Philip Ball. Nature (June 25, 2003). "Computer software develops more effectively when its code is freely accessible to all, UK researchers have calculated. ... Open-access software arose in the early 1990s, during the infancy of the Internet and the World-Wide Web. It challenged the design philosophy behind almost all complex engineering systems." AITopics/Sports
News Scan Briefs. By Charles Q. Choi, JR Minkel, and Gary Stix. Scientific Computer predicts sports injuries - Italian soccer powerhouse looks to artificial intelligence for edge on the field. By Linda Carroll. MSNB (May 29, 2002). "For years team doctors and coaches have looked for crystal balls that would show ACL injuries in the making, soothsayers who could hold forth on hamstrings that might blow, genies that could warn of a rotor cuff about to explode in the new hot prospect's shoulder. AC Milan may have found such an oracle: a computer smart enough to recognize the signs of an athlete coming apart. The renowned Italian soccer club -- which has four players competing in this year's World Cup -- has teamed up with Computer Associates International to test the feasibility of using neural networks, a form of artificial intelligence, to predict injuries and optimize conditioning for each athlete, perhaps even to help select which players to sign. ... The pilot program showed that injury prediction was a possibility, [Jean Pierre] Meersseman said. 'We had information from more than 5,000 tests on our players done over the last four years,' he explained. 'We put this into the network to see if certain parameters changed before a player was injured.' Ultimately the neural network correctly predicted injuries 84 percent of the time, Meersseman said. 'The mathematicians think they can get this number up to 96 percent,' he added." Logging On for Better Fitness - Amateur Athletes Paying for Professional Coaching Online. By Paul Roberts. Special to ABCNEWS.com (January 10, 2001). "Welcome to the burgeoning world of online personal coaching. Thanks to a strong economy, a resurgence in endurance sports and fitness, and the convenience of the Internet, the personal trainer is being transformed from a niche luxury to mainstream commodity via cyberspace. With the new technology, says Carmichael, "we're able to take the same level of training expertise used by professional athletes and deliver it to a much broader audience. ... [C]ompanies are also hard at work on even more sophisticated Web tools that actually 'coach' clients with Artificial Intelligence." PAT, an Interactive Virtual Personal Aerobics Trainer. James W. Davis, Dept. of Computer and Information Science, Ohio State University. "This system moves beyond the highly un-interactive media forms of video tapes and TV shows by having the system watch and respond to the user (instead of just the user watching the TV). We feel that many future systems will be more interactive and less passive, and that perhaps one day will be commonplace within the home environment. Depending on the mood of the user, the choice of instructor could make a large difference in the workout. For instance, if the user were tired and required strong motivation during the workout, a brash Army Drill Sargent as the instructor would make an ideal choice. Along those lines, the prototype system here makes available an Army Drill Sargent character as the instructor." Computer skills come to fore. By Tess Livingstone. The Courier-Mail (October 19, 2004). "University of Queensland Master of Philosophy student Andrew Smith admits he plays golf 'badly', with a handicap of 26. He hopes, after completing his degree, to reduce that to single figures with the help of a new coaching package he's developing as part of his studies. Mr Smith is working to create advanced computer software that sees and assesses the golfer in action and can automatically tell him or her when their posture is wrong or when they've hit the ball badly and why. ... He said his system was one of many applications for computer vision technology in areas such as health rehabilitation, sports training and security." The Droids of Sport - Robotic competitions are popping up around the world. A new book, ‘Gearheads,’ examines their universe. By Brad Stone. Newsweek / available from MSNBC (March 24, 2003). "In March of 2004, teams of roboticists, off-road enthusiasts and garage gearheads will set out in a giant caravan on the same potentially lucrative journey attempted by countless others over the years: the drive from L.A. to Las Vegas. But this time the trip will be far more difficult. The vehicles at the head of the procession will be unmanned, autonomous robots, racing against each other and the clock for a $1 million prize offered by the U.S. military. ... The first formal robot competition took place 32 years ago in the hallways of MIT as part of a mechanical-engineering class called 2.70. ... From there, robot competitions proliferated. In 1989, inspired by 2.70, Segway inventor Dean Kamen started FIRST (For Inspiration and Recognition of Science and Technology), a robotics competition for high schoolers and their mentors. ... Teams are also competing this spring around the world in the regional contests of the fifth annual RoboCup, a robotic soccer tournament." Robolympics contestants shoot for gold - First all-round robotics competition kicks off in San Francisco. By Helen Pearson. Nature Science Update (March 18, 2004). "Like the human version, the Robolympics will put its contestants through a variety of gruelling events, from robot sumo to robot soccer. There is even a robo-triathlon, in which automatons scramble to be first on legs, on wheels and across water." AITopics/Telecommunications
Telecom fraud - Phreaking on the Rise. By Marina Bidoli. Financial Mail SA (January 17, 2003). "Phone pirates who operate illegal 'exchanges' by tapping into private and public telephone lines cost Telkom R174m in stolen call time in the past financial year. The figure is below the international norm. Worldwide phone 'phreaking' is on the increase. Telecom fraud has been identified as the single biggest cause of revenue loss for network providers, averaging between 3%-5% of an operator's annual revenue, says Dimension Data GM for service provider solutions Sean Taylor. At a global loss estimated at US$55bn/year, telecom fraud is bigger business than international drug trafficking. ... Telkom has been working hard to stop this practice. Its fraud-management system analyses calling patterns and abnormalities using a combination of rules and artificial intelligence to detect irregular behaviour. It also has a team of investigators countrywide who take immediate action." At the technology sharp end - In these days of constraint and focus, do carriers still have room for research laboratories? Hugh Bradlow thinks so, but then he runs one. Telstra’s CTO speaks to Robert Clark about how research groups today pay their way. Telecom Asia (March 1, 2004). "[Q] Is speech recognition the one that works for the Telstra's directory inquiries IVR? [A] Now, the expectation is that these natural language speech systems will become increasingly deployed because they offer some really significant advantages, both from the point of view of productivity and from the customer perspective. ... It's a hell of a lot easier than punching your way through an IVR system. But the grammar development is time-consuming, and at the moment it requires specialized expertise and that complicates the deployment. What we've developed is a very interesting tool, developed by one of our staff members who's actually doing a PhD on the topic. He’s come up with a way of actually doing grammar inference. Instead of having to have someone program the grammar in it, he's developed a tool where you can give it examples of the grammar and it will start to learn the grammar. ... [Q ] You've got a very broad range of research topics -- artificial intelligence, Internet systems and architecture. Are any of these bigger or given more resources or priority than others? ... [A] No, my joke is: you name it, we do it...." "Nortel Networks Fraud Solutions is a business unit within the Nortel Networks Corporation, specialising in advanced software and artificial intelligence (AI) technologies. Established in 1997, NNFS is committed to helping operators minimise exposure to telecoms fraud, thereby helping to maximise profits." One of the many interesting pages offered at the site is: "What is Fraud" (An Introduction to Telecommunications Fraud). Bits & Pixels, a company that specializes in the area of Intelligent Agent applications, has a home page with links to many examples of their technology at work in the field of telecommunications. For example, see:
AITopics/TransportationAndShippingexplore iCar technology using an interactive car, Transportation Projects at the Artificial Intelligence Laboratory at the University of Illinois, Chicago. "ITS (Intelligent Transportation Systems) involves improving our existing roadway transportation system through the use of information technology. The AI Lab's interests are in how best to gather, process and disseminate this information to the public's greatest benefit. So far, our efforts have concentrated on three main areas: ADVANCE, GCM, and Data Fusion." Be sure to click on the "Chicagoland Traffic" link in the sidebar on the left. CarSim - Development of a Text-to-Scene Converter for Vehicle Accident Reports. Center for Applied Software Research, Lund Institute of Technology. "The proposed project - CarSim 3.0 - aims at converting automatically textual descriptions of accidents into animated three-dimensional scenes. It will combine language processing and visualization techniques. The system will take a written report describing an accident as input. A first module will analyze the report using information extraction techniques and produce a tabulated representation of it. The resulting information will be passed to a visualization module that will construct a 3D scene with the vehicles and animate them to replay symbolically the accident. ... The CarSim 3.0 platform will be designed to be support tool for analysts of motor vehicle accidents and a production tool of animated graphics for the education of drivers. Its purpose is to help understand the accident conditions by extracting automatically pieces of information from the texts and presenting visually the settings and the movements of the vehicles. It should enable analysts to extract faster exhaustive statistics from a corpus of texts that would not have been entered in a tabulated database format before, to improve the perception of dangerous roads and possibly correct their layout or sign posting using design tools for civil engineering. It should also improve the knowledge of drivers by showing them visually the circumstances of fatal accidents." Ford, NASA bring artificial intelligence to cars and trucks. Ford Motor Company News Release in Florida Today Space Online. September 14, 1998. "Ford Motor Company and NASA's Jet Propulsion Laboratory are bringing artificial intelligence to trucks and cars. A new neural network computer chip that mimics the human mind promises to reduce vehicle emissions and improve fuel economy by monitoring fuel combustion. The neural network chip, designed by computer scientists at NASA's Jet Propulsion Laboratory (JPL) and licensed by Ford Motor Company, has the potential to augment current vehicle on-board diagnostic systems." Intelligent Transportation Systems and Highway Infrastructure. Transport Canada. (October 1996). "This document describes intelligent transportation systems (ITS), current Canadian experiences and international trends with respect to the development and implementation of such systems, and reports on an exploratory assessment of the expected economic payoffs from implementation of key ITS applications in Canada. ITS is the term used to describe a variety of evolving technologies that offer new solutions to improving transportation conditions. These systems -- based on electronic technologies, communications, information processing and navigation technologies -- are revolutionizing the interfaces between the driver, vehicle, and roadway. ITS presents an opportunity to make roads safer, more efficient, more reliable and environmentally friendly, without having to physically alter the highway infrastructure." Smart Highway Idea Advances, but at Only a Rush-Hour Pace. By Ralph Vartabedian. The Los Angeles Times (May 30, 2001). "In congressional testimony on May 10, Transportation Secretary Norman Mineta said the Bush administration proposes to increase funding for intelligent highway systems by 32% to $253 million for fiscal year 2002. 'Intelligent transportation systems and operations can make a difference in how we attack the congestion and productivity problems,' Mineta said. Whether that is a political difference or a real one is anybody's guess. But progress in at least some of the technologies, funded by both government and private industry, is starting to show up. Adaptive cruise control, which automatically detects slower-moving cars ahead and reduces vehicle speed, is beginning to appear in some luxury vehicles and will show up more broadly in the years ahead." "Ascent's SmartAirport Operations Center, the air-transportation industry's leading collaborative decision-support and information-management system for airports, provides total resource visibility and effective resource management to your entire organization. ... SmartAirport Operations Center is at work all over the world, using leading-edge technologies, including Artificial Intelligence and mathematical optimization technologies, to allocate slots, build schedules, track flights, assign parking positions for aircraft, allocate baggage belts, check-in counters, and departure lounges, manage flight readiness, and allocate ground personnel, such as security staff, customer-service agents, ramp workers, and maintenance staff." ITS World Congress (Intelligent Transport Systems World Congress): "Since its launch in 1994, the goal of the annual ITS World Congress has been to encourage and enable the exchange of information on every aspect of ITS deployment." AITopics/TributesIn Memoriam - Yale Psychology Professor Robert Abelson. Yale University press release, July 29, 2005: " "Robert Abelson, retired Eugene Higgins Professor of Psychology and professor of political science at Yale, died July 13 at Hamden Health Care Center of pneumonia brought on by Parkinson's Disease. He was 76. ... In his book 'Scripts, Plans, Goals, and Understanding' ( with Robert Schank 1977), a Citation Classic, he contributed a social psychological perspective to the emerging field of artificial intelligence."
Kenneth M. Colby; Psychiatrist Was Computer Therapy Pioneer. By Myrna Oliver. The Los Angeles Times, May 10, 2001. "His first foray into combining [psychiatry and computer science] came in the late 1960s, when he was working at Stanford University under a career scientist research fellowship from the National Institute of Mental Health. Heading a team of graduate students, Colby created PARRY, a computer model of paranoid thinking, in the Stanford Artificial Intelligence Laboratory." Alistair Holden; UW professor pioneered artificial intelligence. By Carole Beers. Seattle Times (February 9, 1999). "'He was one of the people who brought the study of computer science to the University of Washington and helped created the program,' said Ed Lazowska, computer science and engineering department chair. 'Internationally, he was one of the founders of the field of artificial intelligence. He constantly pumped energy into the young people in the field.' Mr. Holden chaired the first International Joint Conference on Artificial Intelligence in 1969 in Washington, D.C. ... Mr. Holden began the Minority Introduction to Engineering (MITE) program at the UW, said his daughter, Marte Menz of Mercer Island. 'It was a summer program for high-achieving minority high-school students that were interested in engineering. He did that for 20 years until just last summer.'"
AITopics/Uncertainty
Reasoning under Uncertainty in Medical Decision-Support Systems. From the Center for Advanced Medical Informatics at Stanford (CAMIS). "Medicine is replete with uncertainty. In particular, there is uncertainty due to incomplete and inexact scientific models of human health and disease, and there is uncertainty secondary to incomplete and erroneous data about individual patients. We are exploring the use of probability theory as a representation of uncertainty in medical diagnostic systems." AITopics/VideoGamesAndToysTwo reports from Discovery Channel Canada's AI mini-site by Vanessa Ho (July 27, 2001): Giving video games a brA.I.n: "Like the Scarecrow in The Wizard of Oz, computer video games have been in search of a brain since their inception. Enter artificial intelligence (A.I.) Essentially, A.I. allows a computer character to think for 'himself' or 'herself' instead of being based on pre-programmed actions." & Video games that use A.I.: "For years, artificial intelligence has helped make games from chess to poker more of a challenge. More recently, video game designers have been using A.I. to liven-up some of the newest interactive games on the market. Here are a few examples:...." Pleo the lifelike robot was born in Eagle - New toy from co-inventor of Furby already creating buzz for its charismatic behavior. By Ken Dey. Idaho Statesman (September 14, 2006). "Idaho, say hello to Pleo -- a week-old Camarsaurus dinosaur from the Jurassic era. ... Pleo isn't alive, but you wouldn't know it by his charismatic performance. And inventor Caleb Chung is hoping people connect to Pleo like they would a kitten or a puppy when the $250 toy hits the market next spring. Chung knows a few things about bringing toys to life. Chung has worked at big companies like Mattel and holds more than 20 patents. ... Chung hopes Pleo will take the fascination of Furby a step further and help people embrace the concept of artificial intelligence by showing robots with the most human trait of all: emotion. ... Neena Buck, an analyst with Strategy Analytics, an industry market research firm, said similar robotic products on the market, such as Robosapien and the Roboraptor, don't appear to have Pleo's emotional connection. Pleo is more a pet than a robot, she said. ... Whether that realism will pay off in sales remains to be seen. But Chung AIBO - The Entertainment Robo-Dog from Sony. [Note: "This page will close at the end of March 2007 as [Sony's] AIBO product has been discontinued." See article below.]
AI gets down to business. By Matthew Broersma. ZDNet UK. (January 23, 2001). "One very big business in which AI plays a key role is the video-game industry, comparable to the film business in size. Unlike in the movies, it's often up to a computer or game console to create a sense of reality for the gamer, and standards of realism are going up all the time."
How To Start with Gaming AI. By James Matthews. From Generation5. "Gaming AI is definitely one of the most interesting areas of Artificial Intelligence, since it can have immediately noticeable effects. Yet, the biggest problem with programming game AI, is that you often have to program a game to go with it! This is too much trouble for many people, so this article will help you look at various ways to overcome these difficulties." CRESS. Centre for Research on Simulation in the Social Sciences. "Many computer games are, in effect, artificial societies, although they are of course constructed for entertainment rather than for analytical understanding. Some artificial life simulations are also mainly of interest because they are artificial societies." -from their Overview The Restaurant Game - Contribute to the first collaboratively authored computer game and earn Game Designer credit! |
