Jan 12, 2021 · First, continuation helps the challenging optimization landscape of policy gradient methods even when exact/true gradient is available; second, ...
ABSTRACT. Many real-world applications of reinforcement learning (RL) require the agent to learn from a fixed set of trajectories, without collecting new ...
ABSTRACT. Many real-world applications of reinforcement learning (RL) require the agent to learn from a fixed set of trajectories, without collecting new ...
In this work, we propose a simple yet effective policy iteration approach to batch RL using global optimization techniques known as continuation. By ...
Batch Reinforcement Learning through Continuation Method. Yijie Guo, Shengyu Feng, Nicolas Le Roux, Ed Chi, Honglak Lee, Minmin Chen. October 2020 Poster.
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Duration: 5:34
Posted: May 9, 2021
Posted: May 9, 2021
This chapter introduces the basic principles and the theory behind batch reinforcement learning, the most important algorithms, exemplarily discuss ongoing ...
Minmin Chen. Latest. Batch Reinforcement Learning through Continuation Method. Powered by the Academic theme for Hugo. Cite. ×. Copy Download.
Feb 18, 2021 · We propose an algorithm for batch RL, where effective policies are learned using only a fixed offline dataset instead of online interactions ...
Missing: Continuation | Show results with:Continuation
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