This book applies the latest techniques in the fledgling field of artificial intelligence - specifically the new area of soft computing - to the difficult task of dealing with inexact knowledge in an enterprise systems environment. This pragmatic book for managers, administrators, and analysts introduces methods of handling uncertainty and shows how to apply them through programs and examples, including typical enterprise situations. All techniques are supported by their computational equivalents, which are based on the theory of evidence, often referred to as the Dempster-Shafer Theory. Other methods of handling uncertainty are considered, including fuzzy concepts, Bayesian analysis, and the use of certainty factors. "Managing Uncertainty" demonstrates how techniques can be applied in three distinct but related ways - to what has happened in the past, to what is currently happening and to what will happen. Accordingly, the book covers the major areas of induction, inference and prediction. Background information on AI, qualitative information management and belief systems is provided to enhance understanding of the technologies that follow.
This book should be of interest to managers, administrators and analysts.