Abstract
We propose a self-tuning fuzzy controller with virus-evolutionary genetic algorithm(VEGA). This learning algorithm is based on the virus theory of evolution. The VEGA can reduce the number of fuzzy rules by reverse transcription operator and transduction operator. The effectiveness of the proposed method is shown through some simulations of a cart-pole problem.
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