EAGER: Innate Theories in Cognitive Robotics

University Of Utah, Salt Lake City UT

Investigators

Abstract

Research is performed to establish the role of innate theories in cognitive robotics. Current architectures have a major weakness: the semantic levels, although perhaps patterned after biological systems, are selected in an ad hoc way. This project develops domain theories for the following levels of cognitive function: ? self-knowledge: ? dynamical vehicle control: rigid body motion is fundamental to dealing with the physical world, and Lie algebra is used as the key domain theory. ? particular constraints ? rules of the game (e.g., traffic laws): rule-based systems provide the underlying methodology for understanding rules. ? user interaction ? agent behavior: graph eigenvector clustering is used to segment basic behaviors of other agents, including people. ? operational context ? active embodiment computation and communication control: high-level policies on latency, throughput, priority, and parameter selection provide a domain theory. Specifically, the project studies how symmetry theory can be exploited in a novel perception-action architecture. Symmetry plays a deep role in our understanding of the world, in that it addresses issues of invariance. The determination of operators which leave certain aspects of state invariant makes it possible to identify objects or maintain specific constraints while performing other actions. Symmetry operators in signal analysis, concept formation, learning and platform control are studied. The potential impact of the work is a more cohesive, expressive, adaptable and effective cognitive robotics framework. Results will be disseminated at robotics and AI conferences as well as at international workshops (e.g., Schloss Dagstuhl). Potential applications include: cognitive vehicles, sensor networks, buildings, interactive toys, etc.