AAAI Publications, Thirty-First AAAI Conference on Artificial Intelligence

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Optimizing Quantiles in Preference-Based Markov Decision Processes
Hugo Gilbert, Paul Weng, Yan Xu

Last modified: 2017-02-12

Abstract


In the Markov decision process model, policies are usually evaluated by expected cumulative rewards. As this decision criterion is not always suitable, we propose in this paper an algorithm for computing a policy optimal for the quantile criterion. Both finite and infinite horizons are considered. Finally we experimentally evaluate our approach on random MDPs and on a data center control problem.

Keywords


Markov decision process; Quantile

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