Abstract
This chapter discusses the essential optimization problems arising in the realm of fuzzy models and fuzzy modeling and to propose some solutions to the overall design problem. Fuzzy models are regarded as linguistic nonnumeric modeling structures with well-defined functional blocks of input and output interfaces along with a processing module. The chapter elaborates on the essence of fuzzy models, examines the functions of the underlying modules of such models, and specifies the relevant optimization tasks emerging at the level of fuzzy system identification. The chapter also addresses a fundamental question of information granularization along with the issues of nonnumeric–numeric information processing and pertinent encoding-decoding practices. The associated encoding and decoding tasks are formulated and discussed in detail. Considering several distinct levels of conceptual memorization realized within the realm of fuzzy models (subsequently resulting in establishing short-, medium-, and long-term memories), the ensuing learning policies are discussed.
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