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05/22/2023
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice
Mirror descent value iteration (MDVI), an abstraction of Kullback-Leible...
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01/16/2023
The Role of Baselines in Policy Gradient Optimization
We study the effect of baselines in on-policy stochastic policy gradient...
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05/27/2022
KL-Entropy-Regularized RL with a Generative Model is Minimax Optimal
In this work, we consider and analyze the sample complexity of model-fre...
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02/02/2022
On the Effect of Log-Barrier Regularization in Decentralized Softmax Gradient Play in Multiagent Systems
Softmax policy gradient is a popular algorithm for policy optimization i...
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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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05/13/2021
Leveraging Non-uniformity in First-order Non-convex Optimization
Classical global convergence results for first-order methods rely on uni...
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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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07/19/2020
Beyond Prioritized Replay: Sampling States in Model-Based RL via Simulated Priorities
Model-based reinforcement learning (MBRL) can significantly improve samp...
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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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02/14/2020
Frequency-based Search-control in Dyna
Model-based reinforcement learning has been empirically demonstrated as ...
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01/04/2016