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 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.

1101632367
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 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.

54.99 In Stock
Planning and Learning by Analogical Reasoning

Planning and Learning by Analogical Reasoning

by Manuela M. Veloso
Planning and Learning by Analogical Reasoning

Planning and Learning by Analogical Reasoning

by Manuela M. Veloso

Paperback(1994)

$54.99 
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Overview

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.


Product Details

ISBN-13: 9783540588115
Publisher: Springer Berlin Heidelberg
Publication date: 12/27/1994
Series: Lecture Notes in Computer Science , #886
Edition description: 1994
Pages: 190
Product dimensions: 6.10(w) x 9.10(h) x 0.60(d)

Table of Contents

Overview.- The problem solver.- Generation of problem solving cases.- Case storage: Automated indexing.- Efficient case retrieval.- Analogical replay.- Empirical results.- Related work.- Conclusion.
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