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BayesianRiskMarkovDecisionProcesses

Neural Information Processing Systems

Markov decision process (MDP) is a paradigm for modeling sequential decision making under uncertainty. From a modeling perspective, some parameters of MDPs are unknown and need to be estimated from data. In this paper, we consider MDPs where transition probability and cost parametersarenotknown.

Bayesian Risk Markov Decision Processes

Neural Information Processing Systems

Markov decision process (MDP) is a paradigm for modeling sequential decision making under uncertainty. From a modeling perspective, some parameters of MDPs are unknown and need to be estimated from data.