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 1 month 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 (over 7 years ago)
- Default Branch: master
- Last Pushed: 2024-09-19T15:07:33.000Z (8 months ago)
- Last Synced: 2025-04-02T23:14:15.364Z (about 2 months 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: Python
- Homepage:
- Size: 113 MB
- Stars: 182
- Watchers: 9
- Forks: 39
- Open Issues: 1
-
Metadata Files:
- Readme: README.MD
- License: LICENSE