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Exponential Lower Bounds For Policy Iteration
Published 17 Mar 2010 in cs.DS | (1003.3418v1)
Abstract: We study policy iteration for infinite-horizon Markov decision processes. It has recently been shown policy iteration style algorithms have exponential lower bounds in a two player game setting. We extend these lower bounds to Markov decision processes with the total reward and average-reward optimality criteria.
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