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Learning in Tele-autonomous Systems using Soar

Laird, John E. and Yager, Eric S. and Tuck, Christopher M. and Hucka, Michael (1989) Learning in Tele-autonomous Systems using Soar. In: Proceedings of the NASA Conference on Space Telerobotics. NASA Jet Propulsion Laboratory , pp. 415-424.

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Robo-Soar is a high-level robot arm control system implemented in Soar. Robo-Soar learns to perform simple block manipulation tasks using advice from a human. Following learning, the system is able to perform similar tasks without external guidance. Robo-Soar corrects its knowledge by accepting advice about relevance of features in its domain, using a unique integration of analytic and empirical learning techniques.

Item Type:Book Section
Hucka, Michael0000-0001-9105-5960
Additional Information:This research was sponsored by grant NCC2-517 from NASA Ames and ONR grant N00014-88-K-0554. We would like to thank Karen McMahon for implementing Soar 5.0, and Mark Wiesmeyer for developing and implementing the Soar input and output interfaces. Without these extension to Soar, Robo-Soar would not have been possible. We also like to thank the staff of the Robotics Laboratory for help with the tele-autonomous software and hardware. Finally, we thank Paul Rosenbloom and Allen Newell for ideas relating to this work.
Funding AgencyGrant Number
Office of Naval Research (ONR)N00014-88-K-0554
Record Number:CaltechAUTHORS:20130107-150307467
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:36210
Deposited By: Linda Taddeo
Deposited On:07 Jan 2013 23:31
Last Modified:03 Oct 2019 04:35

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