Fuzzy set theory is a mathematical structure for representing uncertainty. Modern intelligent systems must combine knowledge based on techniques for gathering and processing information with methods of approximate reasoning. This enables an intelligent system to better emulate human decision-making in uncertain environments.

Getting Started. Fuzzy Set Theory. Possibility/Probability Consistency Principle. Knowledge Representation. Imprecision and Fuzzy Logic. Knowledge Processing. Knowledge in FEST. Inference Engine. The Fuzzy Inference Engine. Fuzzy Inference in FEST. References. Index.

Fuzzy set theory provides a framework for representing uncertainty. As increasing importance is being given to uncertainty management in intelligent systems, fuzzy inferencing procedures are vital. Using Fest (Fuzzy Expert System Tools), the authors focus on the parameters of fuzzy rule-based systems. The book then goes on to show how Fest can be used for inference of indistinct data and algorithmic descriptions. Divided into three parts, this comprehensive text covers the characteristics of expert systems and fuzzy sets theory, knowledge representation and the inference process. Features include: * Incorporation of uncertainty management and fuzzy logic in soft expert systems * Coverage of the processes of knowledge acquisition, representation, and generation * Novel ideas in approaching fuzzy inferencing * Notions pertaining to flexible grammar and the use of synonyms Written by international experts, this is an invaluable reference for engineers and computer scientists working in the areas of expert systems, fuzzy logic systems and applications of fuzzy logic both in industry and academia. The accompanying disk will allow readers to practice the methods introduced and thus highlight the power of fuzzy logic when combined with expert system technology.