Evolutionary - Based Learning Applied to Fuzzy Controllers . Luis Magdalena , F elix

|Fuzzy Logic Controllers constitute knowledge-based systems that include fuzzy rules and fuzzy membership functions to incorporate the human knowledge into their knowledge base. The deenition of fuzzy rules and fuzzy membership functions is actually aaected by subjective decisions, having a great innuence over the whole FLC performance. Some eeorts have been made to obtain an improvement on system performance by incorporating learning mechanisms to modify rules and/or membership functions. Genetic Algorithms (GAs) are probabilistic search and optimization procedures based on natural genetics. This paper proposes a new way to apply GAs to FLCs, and applies it to a FLC designed to control the Synthesis of biped walk of a simulated 2-D biped robot.