Search Results for author: Larry Rudolph

Found 3 papers, 2 papers with code

Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPO

2 code implementations • 25 May 2020 • Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry

We study the roots of algorithmic progress in deep policy gradient algorithms through a case study on two popular algorithms: Proximal Policy Optimization (PPO) and Trust Region Policy Optimization (TRPO).

reinforcement-learning Reinforcement Learning (RL)

1,111

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Implementation Matters in Deep RL: A Case Study on PPO and TRPO

2 code implementations • ICLR 2020 • Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry

We study the roots of algorithmic progress in deep policy gradient algorithms through a case study on two popular algorithms, Proximal Policy Optimization and Trust Region Policy Optimization.

reinforcement-learning Reinforcement Learning (RL)

110

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Code

A Closer Look at Deep Policy Gradients

no code implementations • ICLR 2020 • Andrew Ilyas, Logan Engstrom, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry

We study how the behavior of deep policy gradient algorithms reflects the conceptual framework motivating their development.

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