AI Seminar @ ISI : "Physical Metaphors for Problem Solving" September 16, 2005

Abstract:

In many domains, physical metaphors are helpful in representing and solving problems. Chess is a well-known example: discussions of strategies commonly describe blocking, pinning, and the general application of force, even though the environment is entirely static.
Physical metaphors of abstract concepts are pervasive in our everyday lives as well.

To explain physical interpretations of abstractions in human thinking, cognitive linguists have developed the concept of image
schemas. Image schemas are general-purpose representations that impose structure on our experiences. Image schemas represent perceptual properties and relationships such as locations, movement, and verticality; they also capture elementary physical operations and structures, such as containment and collection. Image schemas are valuable in that they can provide physical interpretations of non- physical situations.

In this talk I will describe a computational representation of image schemas and discuss the development of an image schema language that can be used to aid problem solving in practical reasoning domains.

Bio:

Rob St. Amant is an associate professor in the Department of Computer Science at North Carolina State University. He is on sabbatical for the 2005 calendar year at ISI, working with Paul Cohen and Carole Beal in the Intelligent Systems Division. His research interests are in intelligent user interfaces and knowledge-based
systems.