Artificial Intelligence and expert systems research, development, and demonstration have rapidly expanded over the past several years; as a result, new terminology is appearing at a phenomenal rate. This sourcebook provides an introduction to artificial intelligence and expert systems, it provides brief definitions, it includes brief descriptions of software products, and vendors, and notes leaders in the field. Extensive support material is provided by delineating points of contact for receiving additional information, acronyms, a detailed bibliography, and other reference data. The terminology includes artificial intelligence and expert system elements for: * Artificial Intelligence * Expert Systems * Natural language Processing * Smart Robots * Machine Vision * Speech Synthesis The Artificial Intelligence and Expert System Sourcebook is compiled from informa tion acquired from numerous books, journals, and authorities in the field of artificial intelligence and expert systems. I hope this compilation of information will help clarify the terminology for artificial intelligence and expert systems' activities. Your comments, revisions, or questions are welcome. V. Daniel Hunt Springfield, Virginia May, 1986 ix Acknowledgments The information in Artificial Intelligence and Expert Systems Sourcebook has been compiled from a wide variety of authorities who are specialists in their respective fields. The following publications were used as the basic technical resources for this book. Portions of these publications may have been used in the book. Those definitions or artwork used have been reproduced with the permission to reprint of the respective publisher.

The first practical guide to using reengineering to dramatically improve the development and success of new products. Executives, product development teams and engineering design groups will see how to consistently execute successful new product launches. In a compelling, clear fashion, Hunt describes how companies can fully integrate their product development process by focusing on seven key initiatives. They include process understanding; broad-based process reengineering; establishing quality goals and multi-functional teams; using the right tools and techniques; and implementing ongoing continuous improvement.