https://github.com/zyxue/rljs
RLjs currently serves as an interactive playground for learning reinforcement learning.
https://github.com/zyxue/rljs
agent algorithm policy-iteration q-learning react reinfrocement-learning rl-algorithms value-iteration
Last synced: 6 months ago
JSON representation
RLjs currently serves as an interactive playground for learning reinforcement learning.
- Host: GitHub
- URL: https://github.com/zyxue/rljs
- Owner: zyxue
- License: mit
- Created: 2017-03-06T03:53:54.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2019-01-07T20:02:10.000Z (over 6 years ago)
- Last Synced: 2025-02-05T10:50:21.627Z (8 months ago)
- Topics: agent, algorithm, policy-iteration, q-learning, react, reinfrocement-learning, rl-algorithms, value-iteration
- Language: JavaScript
- Homepage: https://rljs.herokuapp.com/
- Size: 1.41 MB
- Stars: 3
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
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README
# RLjs
**RLjs** is forked from [REINFORCEjs](https://github.com/karpathy/reinforcejs)
by [Andrej Karpathy](http://cs.stanford.edu/people/karpathy/), but more
modualized with [React](https://facebook.github.io/react/)
in [ES2015/ES6](https://babeljs.io/learn-es2015/). 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/`](https://github.com/zyxue/reinforcejs/tree/master/src/lib/agents),
which implement key RL algorithms such as dynamic
programming([Chapter 4](https://webdocs.cs.ualberta.ca/~sutton/book/ebook/node40.html)),
Sarsa, Q-Learning
([Chapter 6](https://webdocs.cs.ualberta.ca/~sutton/book/ebook/node60.html),
[Chapter 7](https://webdocs.cs.ualberta.ca/~sutton/book/ebook/node72.html)).
1. 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
## Setup
The development setup is adopted from
[create-react-app](https://github.com/facebookincubator/create-react-app).
```
git clone git@github.com: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
```