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02/21/2023
Adversarial Model for Offline Reinforcement Learning
We propose a novel model-based offline Reinforcement Learning (RL) frame...
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11/08/2022
ARMOR: A Model-based Framework for Improving Arbitrary Baseline Policies with Offline Data
We propose a new model-based offline RL framework, called Adversarial Mo...
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10/09/2022
The Role of Coverage in Online Reinforcement Learning
Coverage conditions – which assert that the data logging distribution ad...
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06/16/2022
Interaction-Grounded Learning with Action-inclusive Feedback
Consider the problem setting of Interaction-Grounded Learning (IGL), in ...
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02/05/2022
Adversarially Trained Actor Critic for Offline Reinforcement Learning
We propose Adversarially Trained Actor Critic (ATAC), a new model-free a...
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06/13/2021
Bellman-consistent Pessimism for Offline Reinforcement Learning
The use of pessimism, when reasoning about datasets lacking exhaustive e...
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06/09/2021
Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning
Recent theoretical work studies sample-efficient reinforcement learning ...
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06/09/2021
Interaction-Grounded Learning
Consider a prosthetic arm, learning to adapt to its user's control signa...
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02/05/2021
Finite Sample Analysis of Minimax Offline Reinforcement Learning: Completeness, Fast Rates and First-Order Efficiency
We offer a theoretical characterization of off-policy evaluation (OPE) i...
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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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08/11/2020
Batch Value-function Approximation with Only Realizability
We solve a long-standing problem in batch reinforcement learning (RL): l...
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03/09/2020
Q^ Approximation Schemes for Batch Reinforcement Learning: A Theoretical Comparison
We prove performance guarantees of two algorithms for approximating Q^ i...
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06/08/2019
Optimal Off-Policy Evaluation for Reinforcement Learning with Marginalized Importance Sampling
Motivated by the many real-world applications of reinforcement learning ...
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05/30/2019
Provably Efficient Q-Learning with Low Switching Cost
We take initial steps in studying PAC-MDP algorithms with limited adapti...
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02/01/2019
Privacy Preserving Off-Policy Evaluation
Many reinforcement learning applications involve the use of data that is...
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09/07/2018