Introduction to expert systems
著者
書誌事項
Introduction to expert systems
(International computer science series)
Addison-Wesley, c1999
3rd ed
大学図書館所蔵 全5件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes bibliographical references and index
内容説明・目次
内容説明
In May 1997, IBM's Deeper Blue defeated the world chess champion Gary Kasparov, showing that an artificial intelligence system can outplay even the most skilled of human experts. Since the first expert systems appeared in the late sixties, we have seen three decades of research and development engineer human knowledge to more practical ends, in a pioneering effort that has integrated diverse areas of cognitive and computer science. Today, expert systems exist in many forms, from medical diagnosis to investment analysis and from counseling to production control.
This third edition of Peter Jackson's best-selling book updates the technological base of expert systems research and embeds those developments in a wide variety of application areas. The earlier chapters have been refocused to take a more practical approach to the basic topics, while the later chapters introduce new topic areas such as case-based reasoning, connectionist systems and hybrid systems. Results in related areas, such as machine learning and reasoning with uncertainty, are also accorded a thorough treatment.
The new edition contains many new examples and exercises, most of which are in CLIPS, a language that combines production rules with object-oriented programming. LISP, PROLOG and C++ are also featured where appropriate. Interesting problems are posed throughout, and are solved in exercises involving the analysis, design and implementation of CLIPS programs.
This book will prove useful to a wide readership including general readers, students and teachers, software engineers and researchers. Its modular structure enables readers to follow a pathway most suited to their needs, providing them with an up-to-date account of expert systems technology.
Peter Jackson is Director of Research at West Group, a division of The Thomson Corporation and the leading provider of information to the US legal market. Peter drives the application of natural language and information retrieval technologies to the information needs of law and business. Previous appointments include Principal Scientist at the McDonnell Douglas Research Laboratories in Saint Louis, Missouri, and Lecturer in the Department of Artificial Intelligence at the University of Edinburgh, Scotland.
目次
1. What Are Expert Systems?
2. An Overview of Artificial Intelligence.
3. Knowledge Representation.
4. Symbolic Computation.
5. Rule-Based Systems.
6. Structured Objects.
7. Object-Oriented Programming.
8. Logic Programming.
9. Representing Uncertainty.
10. Knowledge Acquisition.
11. Heuristic Classification (I).
12. Heuristic Classification (II).
13. Hierarchical Hypothesise and Test.
14. Constructive Problem Solving (I).
15. Constructive Problem Solving (II).
16. Designing for Explanation.
17. Tools for Building Expert Systems.
18. Blackboard Systems.
19. Truth Maintenance Systems.
20. Machine Learning.
21. Belief Networks.
22. Case Based Reasoning.
23. Hybrid Systems.
24. Summary and Conclusion.
Appendix:
CLIPS Programming.
「Nielsen BookData」 より