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07/25/2023
The Optimal Approximation Factors in Misspecified Off-Policy Value Function Estimation
Theoretical guarantees in reinforcement learning (RL) are known to suffe...
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07/18/2022
A Few Expert Queries Suffices for Sample-Efficient RL with Resets and Linear Value Approximation
The current paper studies sample-efficient Reinforcement Learning (RL) i...
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02/03/2021
On Query-efficient Planning in MDPs under Linear Realizability of the Optimal State-value Function
We consider the problem of local planning in fixed-horizon Markov Decisi...
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11/02/2020
A Variant of the Wang-Foster-Kakade Lower Bound for the Discounted Setting
Recently, Wang et al. (2020) showed a highly intriguing hardness result ...
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10/03/2020
Exponential Lower Bounds for Planning in MDPs With Linearly-Realizable Optimal Action-Value Functions
We consider the problem of local planning in fixed-horizon Markov Decisi...
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08/26/2020
Constrained Markov Decision Processes via Backward Value Functions
Although Reinforcement Learning (RL) algorithms have found tremendous su...
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03/27/2020
A Distributional Analysis of Sampling-Based Reinforcement Learning Algorithms
We present a distributional approach to theoretical analyses of reinforc...
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06/21/2018