Introduction To Expert Systems (3rd Edition)

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9780201876864: Introduction To Expert Systems (3rd Edition)

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.

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Review:

Written for the computer science student or more advanced developer interested in expert systems, the new edition of Peter Jackson's Introduction to Expert Systems provides a truly magisterial tour of several decades of artificial intelligence (AI) and expert system research. This comprehensive book compiles past efforts to get computers to reason like experts as well as explaining how today's expert systems work.

The notable strength of this title is the author's impressive command of the computer science literature in the field of AI and expert systems. In chapter after chapter, the author reviews research-quality (and some production-level) projects that have attempted to reproduce human expertise using computers in such areas as medical diagnosis. Besides explaining essential expert system topics such as knowledge representation and the rules used for arriving at decisions, this book also provides numerous samples using the CLIPS programming language.

This textbook-style treatment of this subject features plenty of mathematical notation (such as the propositional calculus) and exercises at the end to stimulate your own thinking. For the general reader, the author's explanation of the history of AI (which has offered mixed results in the face of high expectations in the 1980s, for instance) is quite accessible and probably worth the price of the book. Rich with detail for the expert, this title shows off the best of expert systems--both in the past and today--as well as the reasonably bright prospects for the future of intelligent machines that think more like human experts. --Richard Dragan

Topics covered: Introduction to expert systems; representing knowledge; history of artificial intelligence (AI) research: Classical, Romantic, and Modern Periods; knowledge representation: STIPS and MYCIN applications; symbolic representation and LISP; rule-based and canonical systems; associative nets and frame systems: graphs, trees, and networks; object-oriented programming and its usefulness in expert systems; programming languages: LOOPS, Flavors, CLOS, CLIPS, C++, and PROLOG; uncertainty and fuzzy logic; knowledge acquisition; heuristic classification; strategies for problem solving; blackboard architectures; machine learning; police networks; case-based reasoning (CBR); hybrid systems; and the future of expert systems.

About the Author:

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.



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