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Proceedings Paper

Toward cognitive robotics
Author(s): John E. Laird
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Paper Abstract

Our long-term goal is to develop autonomous robotic systems that have the cognitive abilities of humans, including communication, coordination, adapting to novel situations, and learning through experience. Our approach rests on the recent integration of the Soar cognitive architecture with both virtual and physical robotic systems. Soar has been used to develop a wide variety of knowledge-rich agents for complex virtual environments, including distributed training environments and interactive computer games. For development and testing in robotic virtual environments, Soar interfaces to a variety of robotic simulators and a simple mobile robot. We have recently made significant extensions to Soar that add new memories and new non-symbolic reasoning to Soar's original symbolic processing, which should significantly improve Soar abilities for control of robots. These extensions include episodic memory, semantic memory, reinforcement learning, and mental imagery. Episodic memory and semantic memory support the learning and recalling of prior events and situations as well as facts about the world. Reinforcement learning provides the ability of the system to tune its procedural knowledge - knowledge about how to do things. Mental imagery supports the use of diagrammatic and visual representations that are critical to support spatial reasoning. We speculate on the future of unmanned systems and the need for cognitive robotics to support dynamic instruction and taskability.

Paper Details

Date Published: 30 April 2009
PDF: 11 pages
Proc. SPIE 7332, Unmanned Systems Technology XI, 73320Z (30 April 2009); doi: 10.1117/12.818701
Show Author Affiliations
John E. Laird, Univ. of Michigan (United States)

Published in SPIE Proceedings Vol. 7332:
Unmanned Systems Technology XI
Grant R. Gerhart; Douglas W. Gage; Charles M. Shoemaker, Editor(s)

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