Introduction to Uncertain Systems

Abstract

Uncertainty is one of the main features of complex and intelligent decision making systems. Various approaches, methods and techniques in this field have been developed for several decades, starting with such concepts and tools as adaptation, stochastic optimization and statistical decision theory (see e.g. [2, 3, 68, 79, 80]). The first period of this development was devoted to systems described by traditional mathematical models with unknown parameters. In the past two decades new ideas (such as learning, soft computing, linguistic descriptions and many others) have been developed as a part of modern foundations of knowledge-based Decision Support Systems (DSS) in which the decisions are based on uncertain knowledge. Methods and algorithms of decision making under uncertainty are especially important for design of computer control and management systems based on incomplete or imperfect knowledge of a decision plant. Consequently, problems of analysis and decision making in uncertain systems are related to the following fields:

• 1. General systems theory and engineering.

• 2. Control and management systems.

• 3. Information technology (knowledge-based expert systems).