Planning and Learning by Analogical Reasoning [electronic resource] / edited by Manuela M. Veloso.
Material type: TextSeries: Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence ; 886Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 1994Description: XIV, 190 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783540491095Subject(s): Computer science | Electronic data processing | Computer Science | Computing MethodologiesAdditional physical formats: Printed edition:: No titleDDC classification: 006 LOC classification: QA75.5-76.95Online resources: Click here to access onlineCurrent library | Home library | Call number | Materials specified | URL | Status | Date due | Barcode |
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IMSc Library | IMSc Library | Link to resource | Available | EBK6663 |
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.
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