43 citations · 46 across the 5 of their papers we have counts for
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cs.LG2021★ 3 cited
Optimistic Policy Optimization is Provably Efficient in Non-stationary MDPs
Han Zhong, Zhongren Chen, Zhuoran Yang +2
We study episodic reinforcement learning (RL) in non-stationary linear kernel Markov decision processes (MDPs). In this setting, both the reward function and the transition kernel…
cs.LG2021
TensorPlan and the Few Actions Lower Bound for Planning in MDPs under Linear Realizability of Optimal Value Functions
Gellért Weisz, Csaba Szepesvári, András György
We consider the minimax query complexity of online planning with a generative model in fixed-horizon Markov decision processes (MDPs) with linear function approximation. Following…