https://github.com/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
https://github.com/nasdin/reinforcementlearning-atarigame

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

Last synced: about 5 hours ago
JSON representation

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

• Host: GitHub
• URL: https://github.com/nasdin/reinforcementlearning-atarigame
• Owner: Nasdin
• License: bsd-3-clause
• Created: 2017-09-27T02:31:42.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2019-02-27T14:08:43.000Z (over 5 years ago)
• Last Synced: 2023-10-20T21:59:08.306Z (about 1 year ago)
• Topics: a3c, a3c-lstm, actor-critic, adam, asynchronous-advantage-actor-critic, deep-reinforcement-learning, lstm, openai-gym, python, pytorch, reinforcement-agents, reinforcement-learning, reinforcement-learning-algorithms, rmsprop, universe
• Language: Jupyter Notebook
• Homepage:
• Size: 90.6 MB
• Stars: 164
• Watchers: 10
• Forks: 39
• Open Issues: 1
• Metadata Files:
  • Readme: README.MD
  • License: LICENSE

Awesome Lists containing this project