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Implementation Matters in Deep Policy Gradients: A Case ...
arXiv
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由 L Engstrom 著作2020被引用 272 次 — We study the roots of algorithmic progress in deep policy gradient algorithms through a case study on two popular algorithms: Proximal Policy Optimization (PPO ...
Implementation Matters in Deep RL: A Case Study on PPO ...
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由 L Engstrom 著作被引用 318 次 — We study the roots of algorithmic progress in deep policy gradient algorithms through a case study on two popular algorithms: Proximal Policy Optimization (PPO ...
Implementation Matters in Deep RL: A Case Study on PPO ...
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A case study on PPO and TRPO. Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry.
Implementation Matters in Deep RL: A Case Study on PPO ...
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Our results show that they (a) are responsible for most of PPO's gain in cumulative reward over TRPO, and (b) fundamentally change how RL methods function.
Implementation Matters in Deep RL: A Case Study on PPO ...
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2020年1月14日 — PPO is based on Trust Region Policy Optimization (TRPO), an algorithm that constrains the KL divergence between successive policies on the optimization ...
Implementation Matters in Deep RL: A Case Study on PPO ...
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2019年9月25日 — We study the roots of algorithmic progress in deep policy gradient algorithms through a case study on two popular algorithms: Proximal Policy Optimization (PPO ...
A Case Study on PPO and TRPO - 穷酸秀才大草包
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2023年3月23日 — 穷酸秀才大艹包. 上海交通大学CS博士生. Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPO.
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Implementation Matters in Deep RL: A Case Study on PPO ...
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The results show that algorithm augmentations found only in implementations or described as auxiliary details to the core algorithm are responsible for most ...
A Case Study on PPO and TRPO - Gradient
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We study the roots of algorithmic progress in deep policy gradient algorithms through a case study on two popular algorithms: Proximal Policy Optimization ...
A Case Study on PPO and TRPO
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View recent discussion. Abstract: We study the roots of algorithmic progress in deep policy gradient algorithms through a case study on two popular ...