This repository is a study of interesting characteristics of the robust value iteration algorithm. In particular, we introduce RPVL in our paper which considers finite-horizon tabular MDP. Gambler's problem (or Gambler's Ruin) is a simple yet nice example for us to characterize the behavior of an optimal robust policy.
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Code for Improved Sample Complexity Bounds for Distributionally Robust Reinforcement Learning [AISTATS'23]
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zaiyan-x/RPVL
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Code for Improved Sample Complexity Bounds for Distributionally Robust Reinforcement Learning [AISTATS'23]
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