Incremental best estimate directed search - a case study for symmetrical systems

This paper studies the performance of an incremental best-estimate-directed search (IBEDS) for symmetrical systems. IBEDS is a bootstrappable search algorithm designed for controller optimization. The idea is to make the training set and the rule base symmetric. By doing so, the the searching of IBEDS is expedited. The presented simulation results justify the method.

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