Integrated Intelligent Capabilities Special Track
To solve complex, real-world problems, AI systems often must integrate a variety of component technologies, such as vision, classification, speech, memory, language, dialogue, planning, problem solving, learning, and goal-driven action. Robots, autonomous software agents, and intelligent tutoring systems with natural language dialogue are prototypical examples of these integrated intelligent systems. Some, but not all, of these integrated intelligent systems are inspired by theories in cognitive science and biological systems.
Papers in this track report on theoretical and/or empirical studies that highlight the role of integration of multiple components in achieving intelligent behavior. They articulate the mechanisms for integrating multiple components and the salient characteristics of individual components that facilitate such integration.
The list of papers to be presented at AAAI-06 can be found in the AAAI-06 proceedings.
Cochairs:
Art Graesser, University of Memphis
Reid Simmons, Carnegie Mellon University
Reviewers:
Gautam Biswas, Vanderbilt University
Chris Forsythe, Sandia National Laboratories
Stan Franklin, University of Memphis
Khan Iftekharuddin, University of Memphis
Pamela Jordon, University of Pittsburgh
John Laird, University of Michigan
David Kortenkamp, NASA Johnson Space Center
Francois Michaud, Université de Sherbrooke
Nicola Muscettola, NASA Ames Research Center
Andrew Olney, University of Memphis
Helen Pain, School of Informatics at The University of Edinburgh
Kanna Rajan, Monterey Bay Aquarium Research Institute
Deb Roy, MIT Media Laboratory
Paul Rybski, Carnegie Mellon University
Aaron Sloman, The University of Birmingham
Amy Soller, Institute for Defense Analyses
Greg Trafton, Naval Research Laboratory
Hannes Vilhjalmsson, Information Sciences Institute
Peter Wiemer-Hastings, DePaul University
Holly Yanco, University of Massachusetts Lowell