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10/12/2022
Reinforcement Learning with Automated Auxiliary Loss Search
A good state representation is crucial to solving complicated reinforcem...
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09/07/2022
On the Convergence of Monte Carlo UCB for Random-Length Episodic MDPs
In reinforcement learning, Monte Carlo algorithms update the Q function ...
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02/17/2022
VRL3: A Data-Driven Framework for Visual Deep Reinforcement Learning
We propose a simple but powerful data-driven framework for solving highl...
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11/17/2021
Aggressive Q-Learning with Ensembles: Achieving Both High Sample Efficiency and High Asymptotic Performance
Recently, Truncated Quantile Critics (TQC), using distributional represe...
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01/15/2021
Randomized Ensembled Double Q-Learning: Learning Fast Without a Model
Using a high Update-To-Data (UTD) ratio, model-based methods have recent...
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02/10/2020
On the Convergence of the Monte Carlo Exploring Starts Algorithm for Reinforcement Learning
A simple and natural algorithm for reinforcement learning is Monte Carlo...
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10/27/2019
BAIL: Best-Action Imitation Learning for Batch Deep Reinforcement Learning
The field of Deep Reinforcement Learning (DRL) has recently seen a surge...
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10/05/2019
Towards Simplicity in Deep Reinforcement Learning: Streamlined Off-Policy Learning
The field of Deep Reinforcement Learning (DRL) has recently seen a surge...
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06/10/2019
