Rule-Based Expert Systems: MYCIN Experiments of Stanford Heuristic Programming

Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project Edited by Bruce G. Buchanan and Edward H. Shortliffe 754 pp., references, index, illus. electronic text Addison Wesley, Reading, MA, 1984 Out of print. All chapters are freely available below. Artificial intelligence, or AI, is largely an experimental science—at least as much progress has been made by building and analyzing programs as by examining theoretical questions. MYCIN is one of several well-known programs that embody some intelligence and provide data on the extent to which intelligent behavior can be programmed. As with other AI programs, its development was slow and not always in a forward direction. But we feel we learned some useful lessons in the course of nearly a decade of work on MYCIN and related programs. In this book we share the results of many experiments performed in that time, and we try to paint a coherent picture of the work. The book is intended to be a critical analysis of several pieces of related research, performed by a large number of scientists. We believe that the whole field of AI will benefit from such attempts to take a detailed retrospective look at experiments, for in this way the scientific foundations of the field will gradually be defined. It is for all these reasons that we have prepared this analysis of the MYCIN experiments. Contributors Foreword Allen Newell Preface Part One: Background Chapter 1—The Context of the MYCIN Experiments Chapter 2—The Origin of Rule-Based Systems in AI Randall Davis and Jonathan J. King Part Two: Using Rules Chapter 3—The Evolution of MYCIN’s Rule Form Chapter 4—The Structure of the MYCIN System William van Melle Chapter 5—Details of the Consultation System Edward H. Shortliffe Chapter 6—Details of the Revised Therapy Algorithm William J. Clancey Part Three: Building a Knowledge Base Chapter 7—Knowledge Engineering Chapter 8—Completeness and Consistency in a Rule-Based System Motoi Suwa, A. Carlisle Scott, and Edward H. Shortliffe Chapter 9—Interactive Transfer of Expertise Randall Davis Part Four: Reasoning Under Uncertainty Chapter 10—Uncertainty and Evidential Support Chapter 11—A Model of Inexact Reasoning in Medicine Edward H. Shortliffe and Bruce G. Buchanan Chapter 12—Probabilistic Reasoning and Certainty Factors J. Barclay Adams Chapter 13—The Dempster-Shafer Theory of Evidence Jean Gordon and Edward H. Shortliffe Part Five: Generalizing MYCIN Chapter 14—Use of the MYCIN Inference Engine Chapter 15—EMYCIN: A Knowledge Engineer’s Tool for Constructing Rule-Based Expert Systems William van Melle, Edward H. Shortliffe, and Bruce G. Buchanan Chapter 16—Experience Using EMYCIN James S. Bennett and Robert S. Engelmore Part Six: Explaining the Reasoning Chapter 17—Explanation as a Topic of AI Research Chapter 18—Methods for Generating Explanations A. Carlisle Scott, William J. Clancey, Randall Davis, and Edward H. Shortliffe Chapter 19—Specialized Explanations for Dosage Selection Sharon Wraith Bennett and A. Carlisle Scott Chapter 20—Customized Explanations Using Causal Knowledge Jerold W. Wallis and Edward H. Shortliffe Part Seven: Using Other Representations Chapter 21—Other Representation Frameworks Chapter 22—Extensions to the Rule-Based Formalism for a Monitoring Task Lawrence M. Fagan, John C. Kunz, Edward A. Feigenbaum, and John J. Osborn Chapter 23—A Representation Scheme Using Both Frames and Rules Janice S. Aikins Chapter 24—Another Look at Frames David E. Smith and Jan E. Clayton Part Eight: Tutoring Chapter 25—Intelligent Computer-Aided Instruction Chapter 26—Use of MYCIN’s Rules for Tutoring William J. Clancey Part Nine: Augmenting the Rules Chapter 27—Additional Knowledge Structures Chapter 28—Meta-Level Knowledge Randall Davis and Bruce G. Buchanan Chapter 29—Extensions to Rules for Explanation and Tutoring William J. Clancey Part Ten: Evaluating Performance Chapter 30—The Problem of Evaluation Chapter 31—An Evaluation of MYCIN’s Advice Victor L. Yu, Lawrence M. Fagan, Sharon Wraith Bennett, William J . Clancey, A. Carlisle Scott, John F. Hannigan, Robert L. Blum, Bruce G. Buchanan, and Stanley N. Cohen Part Eleven: Designing for Human Use Chapter 32—Human Engineering of Medical Expert Systems Chapter 33—Strategies for Understanding Structured English Alain Bonnet Chapter 34—An Analysis of Physicians’ Attitudes Randy L. Teach and Edward H. Shortliffe Chapter 35—An Expert System for Oncology Protocol Management Edward H. Shortliffe, A. Carlisle Scott, Miriam B. Bischoff, A. Bruce Campbell, William van MeUe, and Charlotte D. Jacobs Part Twelve: Conclusions Chapter 36—Major Lessons from This Work Epilog Appendix References Name Index Subject Index

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