Abstract
Several architectures have recently been developed which integrate planning, reacting, and knowledge compilation learning, in order to improve system reactivity while retaining system flexibility. This paper assesses strengths and weaknesses of such Plan-Then-Compile architectures, by analyzing one such architecture, Theo-Agent [Mitchell 90]. We describe capabilities and limitations of the Theo-Agent, and use these to try to understand the generic capabilities and limits of Plan-Then-Compile architectures more generally.
Publisher
Association for Computing Machinery (ACM)
Reference4 articles.
1. {Minton et al. ??} Minton S. Carbonell J.G. Knoblock C.A. Kuokka D.R. Etzioni O. and Y. Gil Explanation Based Learning: A Problem Solving Perspective. Artificial Intelligence . Also available as technical report CMU-CS-89--103. 10.1016/0004-3702(89)90047-7 {Minton et al. ??} Minton S. Carbonell J.G. Knoblock C.A. Kuokka D.R. Etzioni O. and Y. Gil Explanation Based Learning: A Problem Solving Perspective. Artificial Intelligence . Also available as technical report CMU-CS-89--103. 10.1016/0004-3702(89)90047-7
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