Nasdin / ReinforcementLearning-AtariGame

Pytorch LSTM RNN for reinforcement learning to play Atari games from OpenAI Universe. We also use Google Deep Mind's Asynchronous Advantage Actor-Critic (A3C) Algorithm. This is much superior and efficient than DQN and obsoletes it. Can play on many games

Date Created 2017-09-27 (7 years ago)

Commits 14 (last one about a month ago)

Stargazers 173 (0 this week)

Watchers 10 (0 this week)

Forks 39

License bsd-3-clause

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RepositoryStats indexes 579,238 repositories, of these Nasdin/ReinforcementLearning-AtariGame is ranked #196,998 (66th percentile) for total stargazers, and #205,652 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #35,108/115,001.

Nasdin/ReinforcementLearning-AtariGame is also tagged with popular topics, for these it's ranked: python (#9,232/21862), pytorch (#2,661/5908), reinforcement-learning (#554/1293), deep-reinforcement-learning (#172/361)

Other Information

Nasdin/ReinforcementLearning-AtariGame has Github issues enabled, there is 1 open issue and 2 closed issues.

All Topics

a3c adam lstm python pytorch rmsprop a3c-lstm universe openai-gym actor-critic reinforcement-agents reinforcement-learning deep-reinforcement-learning reinforcement-learning-algorithms asynchronous-advantage-actor-critic

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2 commits on the default branch (master) since jan '22

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The only known language in this repository is Python

updated: 2024-11-05 @ 01:33pm, id: 104962297 / R_kgDOBkGY-Q