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40 lines
1.5 KiB
Markdown
40 lines
1.5 KiB
Markdown
# 2D Humanoid Walker js
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This project is a reinforcement learning environment for node. You can train a model offline using tensorflow.js then deploy the result to the browser. And example is http://thinkcds.com/2d_walker/.
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## Installation & Usage
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- `git clone https://github.com/wassname/rl_2d_walker.js.git`
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- `npm install`
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- `npm i -g webpack-dev-server webpack`
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- `npm train`: this will train in node
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- you ideally need a CUDA capable GPU with 8GB+ of memory.
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- will take 8 hours to see results, 44 hours for good results
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- `npm start` (in another terminal): this will start a server to view the results. Result will refresh every few hours when a model checkpoint in saved.
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## Modifying
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- The walker contains the physics of the ragdoll: see src/js/walker.js
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- The agent contains the reinforcement learning settings: search for `new DDPGAgent` in src/js/game.js, and also see src/js/ddpg/ddpg_agent.js
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## Contributing
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1. Fork it!
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2. Create your feature branch: `git checkout -b my-new-feature`
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3. Commit your changes: `git commit -am 'Add some feature'`
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4. Push to the branch: `git push origin my-new-feature`
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5. Submit a pull request :D
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# Credits
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- Made by wassname for thinkcds.com
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- The walker code is adapted from <a href="http://rednuht.org/genetic_walkers/">http://rednuht.org/genetic_walkers/</a>
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- DDPG code from metacar
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# Future work
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- [ ] I would like to tweak the strength, stiffness (in box2d this seems to be max torque), friction, etc to allow a more elegant walking behaviour
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- [ ] Clean up the html UI
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