Planning and Learning by Analogical Reasoning
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 scalin...
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| Format: | eBook |
| Language: | English |
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Berlin, Heidelberg
Springer Berlin Heidelberg
1994, 1994
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| Edition: | 1st ed. 1994 |
| Series: | Lecture Notes in Artificial Intelligence
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| Subjects: | |
| Online Access: | |
| Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
| Summary: | 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 |
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| Physical Description: | XIV, 190 p online resource |
| ISBN: | 9783540491095 |