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GitHub / 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

JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Nasdin%2FReinforcementLearning-AtariGame

Stars: 164
Forks: 39
Open Issues: 1

License: bsd-3-clause
Language: Jupyter Notebook
Repo Size: 90.6 MB
Dependencies: 0

Created: over 6 years ago
Updated: 8 months ago
Last pushed: about 5 years ago
Last synced: 7 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

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