uber-research/atari-model-zoo
A binary release of trained deep reinforcement learning models trained in the Atari machine learning benchmark, and a software release that enables easy visualization and analysis of models, and comparison across training algorithms.
This project offers a collection of pre-trained deep reinforcement learning (RL) models that have learned to play Atari games. It provides tools to easily analyze, visualize, and compare how these models make decisions and perform. Researchers studying artificial intelligence and machine learning can use this to better understand and develop new RL agents.
202 stars. No commits in the last 6 months.
Use this if you are a machine learning researcher who wants to examine and understand the behavior of existing deep reinforcement learning agents, without having to train them yourself.
Not ideal if you are looking to train new reinforcement learning models from scratch or develop game-playing agents for non-Atari environments.
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May 25, 2020
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