Case-Based Reasoning

✍ Scribed by Janet Kolodner (Auth.)

• Publisher: Elsevier Inc, Morgan Kaufmann
• Year: 1993
• Tongue: English
• Leaves: 658
• Series: Morgan Kaufmann Series in Representation & Reasoning
• Category: Library

✦ Synopsis

Case-based reasoning is one of the fastest growing areas in the field of knowledge-based systems and this book, authored by a leader in the field, is the first comprehensive text on the subject. Case-based reasoning systems are systems that store information about situations in their memory. As new problems arise, similar situations are searched out to help solve these problems. Problems are understood and inferences are made by finding the closest cases in memory, comparing and contrasting the problem with those cases, making inferences based on those comparisons, and asking questions when inferences can't be made.

This book presents the state of the art in case-based reasoning. The author synthesizes and analyzes a broad range of approaches, with special emphasis on applying case-based reasoning to complex real-world problem-solving tasks such as medical diagnosis, design, conflict resolution, and planning. The author's approach combines cognitive science and engineering, and is based on analysis of both expert and common-sense tasks. Guidelines for building case-based expert systems are provided, such as how to represent knowledge in cases, how to index cases for accessibility, how to implement retrieval processes for efficiency, and how to adapt old solutions to fit new situations.

This book is an excellent text for courses and tutorials on case-based reasoning. It is also a useful resource for computer professionals and cognitive scientists interested in learning more about this fast-growing field.

✦ Table of Contents

Content:
Front Matter, Page i
Copyright, Page ii
Dedication, Page iii
Preface, Pages xiii-xviii
1 - What Is Case-Based Reasoning?, Pages 3-31
2 - Case Studies of Several Case-Based Reasoners, Pages 33-71
3 - Reasoning Using Cases, Pages 73-97
4 - The Cognitive Model, Pages 99-140
Introduction to The Case Library: Representing and Indexing Cases, Pages 141-143
5 - Representing Cases, Pages 145-191
6 - Indexing Vocabulary, Pages 193-245
7 - Methods for Index Selection, Pages 247-281
Introduction to Retrieving Cases from the Case Library, Pages 283-287
8 - Organizational Structures and Retrieval Algorithms, Pages 289-320
9 - Matching and Ranking Cases, Pages 321-368
10 - Indexing and Retrieval, Pages 369-389
Introduction to Using Cases, Page 391
11 - Adaptation Methods and Strategies, Pages 393-437
12 - Controlling Adaptation, Pages 439-468
13 - Using Cases for Interpretation and Evaluation, Pages 469-503
14 - Using Cases: Some Additional Issues, Pages 505-525
Introduction to Pulling It All Together, Page 527
15 - Building a Case-Based Reasoner, Pages 529-561
16 - Conclusions, Opportunities, Challenges, Pages 563-579
Appendix: A Case Library of Case-Based Reasoning Systems, Pages 581-628
Bibliography, Pages 629-649
Index, Pages 651-668