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Correcting and extending domain knowledge using outside guidance

Laird, John E. and Hucka, Michael and Yager, Eric S. and Tuck, Christopher M. (1990) Correcting and extending domain knowledge using outside guidance. In: Proceedings of the Seventh International Conference (1990) on Machine Learning. Morgan Kaufmann Publishers, Inc. , San Mateo, CA, pp. 235-243. ISBN 9781558601413.

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Analytic learning techniques, such as explanation- based learning (EBL), can be powerful methods for acquiring knowledge about a domain where there is a pre-existing theory of the domain. One application of EBL has been to learning apprentice systems where the solution to a problem generated by a human is used as input to the learning process. The learning system analyzes the example and is then able to solve similar problems without outside assistance. One limitation of EBL is that the domain theory must be complete and correct. In this paper we present a general technique for learning from outside guidance that can correct and extend a domain theory. In contrast to hybrid systems that use both analytic and empirical techniques, our approach is completely analytic, using the chunking learning mechanism in the Soar architecture. This technique is demonstrated for a block manipulation task that uses real blocks, a Puma robot arm and a camera vision system.

Item Type:Book Section
Hucka, Michael0000-0001-9105-5960
Additional Information:© 1990 Morgan Kaufmann Publishers, Inc. This research was sponsored by grant NCC2-517 from NASA Ames and ONR grant N00014-88-K-0554.
Funding AgencyGrant Number
Office of Naval Research (ONR)N00014-88-K-0554
Record Number:CaltechAUTHORS:20130107-145622631
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:36209
Deposited By: Linda Taddeo
Deposited On:10 Jan 2013 18:23
Last Modified:03 Oct 2019 04:35

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