Freespace Supports Metacognition for Navigation
Susan L Epstein
2021 Invited Talk
in
Workshop: Metacognition in the Age of AI: Challenges and Opportunities
in
Workshop: Metacognition in the Age of AI: Challenges and Opportunities
Abstract
In a new environment, people identify, remember, and recognize where they can comfortably travel. This paper argues that a robot navigator too should learn and rely upon a mental model of unobstructed space. Extensive simulation of a controller for an industrial-strength robot demonstrates how metacognition applied to a model of unobstructed space resolves some engineering challenges and provides resilience in the face of others. The robot plans and learns quickly, considers alternative actions, takes novel shortcuts, and interrupts its own plans.
Speaker
Susan L Epstein
Professor Epstein is Professor of Computer Science at Hunter College and The Graduate Center of The City University of New York. She studies how brains and minds solve problems, and how a computer can capitalize on that knowledge. Interdisciplinarity is key in her work in knowledge representation and machine learning. She is an Executive Councilor for the Association for the Advancement of Artificial Intelligence, a co-Pi at the National Science Foundation's Center for Brains, Minds, and Machines, and has served as chair of The Cognitive Science Society.
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