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06/09/2023
In-Sample Policy Iteration for Offline Reinforcement Learning
Offline reinforcement learning (RL) seeks to derive an effective control...
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03/16/2023
Conditionally Optimistic Exploration for Cooperative Deep Multi-Agent Reinforcement Learning
Efficient exploration is critical in cooperative deep Multi-Agent Reinfo...
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02/28/2023
The In-Sample Softmax for Offline Reinforcement Learning
Reinforcement learning (RL) agents can leverage batches of previously co...
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12/17/2022
Latent Variable Representation for Reinforcement Learning
Deep latent variable models have achieved significant empirical successe...
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10/29/2021
Understanding the Effect of Stochasticity in Policy Optimization
We study the effect of stochasticity in on-policy policy optimization, a...
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06/18/2021
On the Sample Complexity of Batch Reinforcement Learning with Policy-Induced Data
We study the fundamental question of the sample complexity of learning a...
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04/06/2021
On the Optimality of Batch Policy Optimization Algorithms
Batch policy optimization considers leveraging existing data for policy ...
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05/13/2020
On the Global Convergence Rates of Softmax Policy Gradient Methods
We make three contributions toward better understanding policy gradient ...
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12/24/2019
