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.


Contents

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