2D Humanoid Walker js

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/.

Installation & Usage

• git clone https://github.com/wassname/rl_2d_walker.js.git
• npm install
• npm i -g webpack-dev-server webpack
• npm train: this will train in node
  • you ideally need a CUDA capable GPU with 8GB+ of memory.
  • will take 8 hours to see results, 44 hours for good results
• 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.

Modifying

• The walker contains the physics of the ragdoll: see src/js/walker.js
• 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

Contributing

1. Fork it!
2. Create your feature branch: git checkout -b my-new-feature
3. Commit your changes: git commit -am 'Add some feature'
4. Push to the branch: git push origin my-new-feature
5. Submit a pull request :D

Credits

• Made by wassname for thinkcds.com
• The walker code is adapted from http://rednuht.org/genetic_walkers/
• DDPG code from metacar

Future work

• 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
• Clean up the html UI