The basis of this book is the author’s experience in teaching a senior and graduate course on knowledge engineering. The tools and techniques presented were designed to aid in the development of viable expert systems and are addressed to the novice in this field. This work consists of eight chapters, six of which have been written by different co-authors; four appendices; references; and an index. Each chapter is independent of the others.

Chapter 1 discusses methods of representing knowledge so that if-then type rules may be implemented simply. It also discusses object-attribute-value triples and their relation to tree structures. Chapter 2 deals with a tool for transferring knowledge from a domain expert into a knowledge base. Chapter 3 discusses a tool to eliminate redundant questions from the sequence of system questioning. Chapter 4 is concerned with general-purpose tools that help verify and validate knowledge bases. Chapter 5 discusses a run-time tester. Chapter 6 deals with how to apply sensitivity analysis to an expert system. Chapter 7 considers how to interface with a neural network so that the expert system functions similarly to a rule-based shell. Chapter 8 is a summary of the main points of this volume. Two appendices address thought problems; one of them contains a discussion of possible solutions. Another appendix illustrates an animal classification expert system. A useful glossary is also included. This well-written, succinct introduction would be useful as a supplementary text in an introductory course in knowledge engineering or expert systems that emphasizes construction of an expert system project.