Maximal mean/standard deviation ratio in an undiscounted MDP |
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Authors: | Matthew J Sobel |
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Affiliation: | Georgia Institute of Technology, Atlanta, GA 30332, USA |
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Abstract: | ![]() A stationary policy in an MDP (Markov decision process) induces a stationary probability distribution of the reward from each initial state. The problem analyzed here is maximization of the mean/standard deviation ratio of the stationary distribution. In the unichain case, a solution is obtained via parametric analysis of a linear program having the same number of variables and one more constraint than the formulation for gain-rate optimization. The same linear program suffices in the multichain case if the initial state is an element of choice. The easier problem of maximizing the mean/variance ratio is mentioned at the end of the paper. |
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Keywords: | Markov decision process MDP dynamic program average reward gain-rate undiscounted mean-variance risk-sensitive |
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