---

＜電子ブック＞
Planning and Learning by Analogical Reasoning / by Manuela M. Veloso
(Lecture Notes in Artificial Intelligence. ISSN:29459141 ; 886)

版	1st ed. 1994.
出版者	(Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer)
出版年	1994
本文言語	英語
大きさ	XIV, 190 p : online resource
著者標目	*Veloso, Manuela M author SpringerLink (Online service)
件　名	LCSH:Artificial intelligence LCSH:Computer science FREE:Artificial Intelligence FREE:Theory of Computation
一般注記	Overview -- The problem solver -- Generation of problem solving cases -- Case storage: Automated indexing -- Efficient case retrieval -- Analogical replay -- Empirical results -- Related work -- Conclusion This research monograph describes the integration of analogical and case-based reasoning into general problem solving and planning as a method of speedup learning. The method, based on derivational analogy, has been fully implemented in PRODIGY/ANALOGY and proven in practice to be amenable to scaling up, both in terms of domain and problem complexity. In this work, the strategy-level learning process is cast for the first time as the automation of the complete cycle of construction, storing, retrieving, and flexibly reusing problem solving experience. The algorithms involved are presented in detail and numerous examples are given. Thus the book addresses researchers as well as practitioners HTTP:URL=https://doi.org/10.1007/3-540-58811-6

 類似資料