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We propose a simulation-based algorithm for optimizing the average reward in a Markov Reward Process that depends on a set of parameters. As a special case, the method applies to Markov Decision Processes where optimization takes place within a parametrized set of policies. The algorithm involves the simulation of a single sample path, and can be implemented on-line. A convergence result (with ...

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a chaotic optimization algorithm (coa) based approach for the robust coordinated design of the upfc power oscillation damping controller and the conventional power system stabilizer has been investigated in this paper. chaotic optimization algorithms, which have the features of easy implementation, short execution time and robust mechanisms of escaping from local optimum, is a promising tool fo...