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The Cerebellar Model Articulation Controller (CMAC) is an influentialbrain-inspired computing model in many relevant fields. Since its inception inthe 1970s, the model has been intensively studied and many variants of theprototype, such as Kernel-CMAC, Self-Organizing Map CMAC, and Linguistic CMAC,have been proposed. This review article focus on how the CMAC model isgradually developed and refined to meet the demand of fast, adaptive, androbust control. Two perspective, CMAC as a neural network and CMAC as a tablelook-up technique are presented. Three aspects of the model: the architecture,learning algorithms and applications are discussed. In the end, some potentialfuture research directions on this model are suggested.

A Historical Review of Forty Years of Research on CMAC