Publisher's Synopsis
This book presents an easy-to-read, updated evidence theory and its applications, built on the Dempster-Shafer theory. The Dempster-Shafer theory significantly generalizes classic Bayesian statistics, and has been rapidly developed recently because of its many found applications in a variety of areas such as artificial intelligence, expert systems, information systems, decision making, statistics and mathematics. The volume gives an introduction to the Dempster-Shafer theory, introduces Barnett's methodology to linearize the time complexity of computation of evidential functions, discusses separable mass functions, and deals with rule strengths in expert systems.;This volume is intended for a wide readership, ranging from academics, to engineers, system developers and managers in information systems, computer science, and business management. The guide is adaptable for both lectures and self-study and is intended to strengthen the reader's background and problem solving abilities.
