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19 lines
780 B
Markdown
19 lines
780 B
Markdown
# pytorch-a2c
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This is a PyTorch implementation of Advantage Actor Critic (A2C), a synchronous deterministic version of A3C ["Asynchronous Methods for Deep Reinforcement Learning"](https://arxiv.org/pdf/1602.01783v1.pdf). Also see [the OpenAI post](https://blog.openai.com/baselines-acktr-a2c/) (section A2C and A3C) for more information.
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This implementation is inspired by the [OpenAI A2C baseline](https://github.com/openai/baselines/tree/master/baselines/a2c). It uses the same hyper parameters and the model since they were well tuned for Atari games.
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## Contributions
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Contributions are very welcome. If you know how to make this code better, don't hesitate to send a pull request.
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## Usage
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```
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python main.py --env-name "PongNoFrameskip-v4"
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```
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## Results
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Coming soon.
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