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Learning by Induction

Reasoning by Inferring Generalizations Based on Individual Instances


AITopics > Machine Learning > Learning by Induction

  

Mark of time. The Engineer Online (September 18, 2006). "A pioneering study at Manchester University is using a 'robot scientist' to examine blood samples for biological markers that may diagnose Alzheimer's disease. ... The robot scientist combines the automatic operation of a blood analysis technique called GCGC-MS with artificial intelligence to determine which experiment to carry out next. ... Douglas Kell, a professor of bioanalytical science at Manchester, was one of the developers of the robot scientist. 'The original idea was to automate the process of scientific discovery,' said Kell. 'There is a model by which we alternate the world of ideas with the world of experience. We carry out an experiment then revise our hypothesis in a cyclic loop. The robot scientist can combine working out what experiment is best to do next with actually carrying it out.' ... The robot uses Inductive Logic Programming, a machine learning process. The scientists give it the background knowledge about the experiment, called the domain. It then decides which hypothesis to follow using the available data."

Machine learns games 'like a human.' By Will Knight. New Scientist News (January 24, 2005). "A computer that learns to play a 'scissors, paper, stone' by observing and mimicking human players could lead to machines that automatically learn how to spot an intruder or perform vital maintenance work, say UK researchers. CogVis, developed by scientists at the University of Leeds in Yorkshire, UK, teaches itself how to play the children's game by searching for patterns in video and audio of human players and then building its own 'hypotheses' about the game's rules. In contrast to older artificial intelligence (AI) programs that mimic human behaviour using hard-coded rules, CogVis takes a more human approach, learning through observation and mimicry, the researchers say. ... Chris Needham, another member of the CogVis team, says the system's visual processor analyses the action by separating periods of movement and inactivity and then extracting features based on colour and texture. Combining this with audio input, the system develops hypotheses about the game's rules using an approach known as inductive logic programming." Be sure to see the sidebar with related articles & web sites.

Inductive Logic Programming resources from Professor Stephen H. Muggleton, Head of Computational Bioinformatics Laboratory,Department of Computing, Imperial College London. "Inductive Logic Programming (ILP) is a research area formed at the intersection of Machine Learning and Logic Programming. ILP systems develop predicate descriptions from examples and background knowledge. ... Presently successful applications areas for ILP systems include the learning of structure-activity rules for drug design, finite-element mesh analysis design rules, primary-secondary prediction of protein structure and fault diagnosis rules for satellites."

Accountancy Age Awards 2007 - Best Use of Internet: Business. Accountancy Age (November 15, 2007). "The equivalent of an electronic auditor, Validis, the winner of the Best use of Internet in Business Award, is a revolutionary new software package that uses artificial intelligence technology to pull out discrepancies and errors in small business accountants. ... 'This technology could change the way businesses operate. The use of the internet to deliver the product and the flexible approach is very inventive,' the judges said."

  • How Validis works [excerpt]: "Inductive Logic Programming - Validis technology is based on an exciting new field of artificial intelligence called Inductive Logic Programming. Essentially, ILP allows a piece of software to analyse an extremely complex, highly relational set of data and to generate and test its own ideas about that data. Unlike the linear rules of a typical data mining application, ILP uses First Order Logic to remove intermediate human interpretation steps and drive the investigation on its own."

Although Ray Solomonoff's 1956 paper, An Inductive Inference Machine, is not available online, many of his other publications are.

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Page last modified on January 20, 2012, at 04:44 AM