Planning and learning by analogical reasoning
By: Manuela M. Veloso.
Series: Lecture notes in artificial intelligence ;; 886.; Lecture notes in computer science; Lecture notes in computer science.; Lecture notes in computer science ;; 886.
Publisher: Springer-Verlag; Springer
Published: 1994
Place of publication: Berlin; New York
Language: eng
Number of pages: 181
Subjects: Machine learning; Decision making; Reasoning
Description: "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."--PUBLISHER'S WEBSITE.
Notes: Includes bibliographical references (p. [173]-181).