First published in 1992, this volume identifies the problems facing the designer of multi-environmental knowledge-based systems, and explains the principles that must be followed in order to obtain successful results. Systems called upon to function in a variety of widely differing cultural and natural environments can only do so satisfactorily if from the very beginning they have been designed with this versatility in mind. For the first time, the know-how for this often formidable design task has been gathered together and presented here. This study was written to an overall plan, with chapters commissioned from a group of research of quite diversified back-grounds who had deeply explored their subjects. Each topic was thus covered in close connection with the others, so as to form a coherent whole. While primarily aimed at workers in Artificial Intelligence and Expert Systems, as well as designers of other kinds of sophisticated software, the contents of the book are of wider validity, just as the multi-environmental demands are of wider incidence. Manufactures, exporters and importers of computing technology with a large knowledge component will also find their concerns addressed.

This book focuses on approaches to computer-assisted medical decision-making. A unique feature of the book is that a specific problem in medical decision-making has been selected from the literature, with each contributed chapter presenting a different approach to the solution of the same problem. Theoretical foundations for each approach are provided, followed by practical application. Techniques include knowledge-based reasoning, neural network models, hybrid systems, reasoning with uncertainty, and fuzzy logic, among others. The goal is to supply the reader with a variety of theoretical techniques whose practical implementation can be clearly understood through the example. Using a single, concrete example to illustrate different theoretical approaches allows various techniques to be easily contrasted and permits the reader to determine which aspects are pertinent to specific types of applications. Although the methods are illustrated in a medical problem, they have wide applicability in numerous areas of decision-making.

Knowledge Based Systems (KBS) are systems that use artificial intelligence techniques in the problem solving process. This text is designed to develop an appreciation of KBS and their architecture and to help users understand a broad variety of knowledge based techniques for decision support and planning. It assumes basic computer science skills and a math background that includes set theory, relations, elementary probability, and introductory concepts of artificial intelligence. Each of the 12 chapters are designed to be modular providing instructors with the flexibility to model the book to their own course needs. Exercises are incorporated throughout the text to highlight certain aspects of the material being presented and to stimulate thought and discussion.

This five-volume set clearly manifests the great significance of these key technologies for the new economies of the new millennium. The discussions provide a wealth of practical ideas intended to foster innovation in thought and, consequently, in the further development of technology. Together, they comprise a significant and uniquely comprehensive reference source for research workers, practitioners, computer scientists, academics, students, and others on the international scene for years to come.

Fuzzy Logic for the Management of Uncertainty covers many important topics, including:" "Developments in mathematics that have paved the road for fuzzy logic;" "Deep, and of a broad perspective, exposition of virtually all approaches used in contemporary science for the representation and handling of imperfect (uncertain, imprecise, vague, ambiguous, etc.) information;" "Coverage of practically all relevant and promising directions and approaches in fuzzy logic research including LT--fuzzy logic, model theoretic approaches, intuitionistic fuzzy logic, nonmonotonic fuzzy logic, modifier fuzzy logic;" "VLSI fuzzy logic-based chips that have triggered the implementation of fuzzy logic in so many fields of science and technology;" "A broad coverage of fuzzy logic in approximate reasoning, including basic issues related to the role of fuzzy logic for approximate reasoning, analyses of various definitions of fuzzy implication that is a crucial element in fuzzy logic-based reasoning schemes,

It is in the area of Systems Diagnosis. Supervision and Control that Knowledge-Based Techniques have had their most significant impact in recent years. In this volume. Spyros Tzafestas has ably put together the current state of the art of the application of Artificial Intelligence concepts to problems of Systems Diagnosis. All the authors in this edited work are distinguished internationally. recognized experts on various aspects of Artificial Intelligence and its applications. and the coverage of the field that they provide is both readable and authoritative. The sixteen chapters break down in a natural way into three broad categories i.e •• (a) introduction to the applications of Expert Systems in Engineering. (b) Knowledge-based systems architectures. models and techniques for fault diagnosis. supervision and real time control and finally. (c) applications and case studies in three specific 'areas. namely: Manufacturing. Chemical Processes and Communications Networks. The final chapter provides a com prehensive survey of the field with an extensive bibliography. The mix of original scientific articles. tutorial and survey papers makes this col lection a very timely and valuable addition to the literature in this important field. MADAN G. SINGH Professor of Information Engineering at U.M.I.S.T.