Evidence Theory and Its Applications

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. 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.