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RLjs currently serves as an interactive playground for learning reinforcement learning.

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RLjs

RLjs is forked from REINFORCEjs by Andrej Karpathy, but more modualized with React in ES2015/ES6. It tries to serve mainly as a playground for learning reinforcement learning (RL) related algorithms. The two main parts are:

  1. The agents as in src/lib/agents/, which implement key RL algorithms such as dynamic programming(Chapter 4), Sarsa, Q-Learning (Chapter 6, Chapter 7).
  2. The grid world which is taken as the example to illustrate how different agents/RL algorithms work.

Currently, only tabular methods have been covered. Approximation methods are planned to be developed developed in the future.

The draft app is available at https://rljs.herokuapp.com/.

There is also another repo for hosting machine-learning related notebooks I created when learning/implementing algorithms at https://github.com/zyxue/sutton-barto-rl-exercises.

A screenshot

screenshot

Setup

The development setup is adopted from create-react-app.

git clone [email protected]:zyxue/rljs.git
cd rljs
yarn install

Run server

yarn start

Build

This will generate the static web site and copy it to the docs folder that is deployed to the web site when you push to GitHub.

yarn build

Test

yarn test

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