Call For Volunteers: Due to my lack of time, I'm desperately looking for voluntary help. Should you be interested in building reinforcement agents (even though you're a newbie) and willing to develop this educational project a little further, please contact me :) There are some points on the agenda, that I'd still like to see implemented to make this project a nice library for abstract educational purposes.
INACTIVE: Due to lack of time and help
reinforce-js – a collection of various simple reinforcement learning solver. This library is for educational purposes only. The library is an object-oriented approach and tries to deliver simplified interfaces that make using the algorithms pretty easy (baked with Typescript). More over it is an extension of Andrej Karpathy's reinforcement learning library that implements several common RL algorithms. In particular, the library currently includes:
Currently exposed Classes:
Code-Example and General Information
DQNSolver
- Concrete Deep Q-Learning Solver
DQNOpt
).DQNOpt
- Concrete options of DQNSolver
DQNEnv
- Concrete environment of DQNSolver
Planned to be implemented:
Download available @npm
: reinforce-js
Install via command line:
npm install --save reinforce-js@latest
The project directly ships with the transpiled Javascript code. And for TypeScript development it also contains Map-files and Declaration-files.
These classes can be imported from this npm
module, e.g.:
import { DQNSolver, DQNOpt, DQNEnv } from 'reinforce-js';
For JavaScript usage require
classes from this npm
module as follows:
const DQNSolver = require('reinforce-js').DQNSolver;
const DQNOpt = require('reinforce-js').DQNOpt;
const DQNEnv = require('reinforce-js').DQNEnv;
For the DQN-Solver please visit Learning Agents (GitHub Page).
Everybody is more than welcome to contribute and extend the functionality!
Please feel free to contribute to this project as much as you wish to.
git clone https://github.com/mvrahden/reinforce-js.git
cd
into the directory and npm install
for initializationnpm run test
. If everything is green, you're ready to go :sunglasses:Before triggering a pull-request, please make sure that you've run all the tests via the testing command:
npm run test
This project relies on Visual Studio Codes built-in Typescript linting facilities. Let's follow primarily the Google TypeScript Style-Guide through the included tslint-google.json configuration file.
This Library relies on the object-oriented Deep Recurrent Neural Network library:
Please be aware that this repository is still under construction. Changes are likely to happen. There are still classes to be added, e.g. DPSolver, SimpleReinforcementSolver, RecurrentReinforcementSolver, DeterministPG and their individual Opts and Envs
As of License-File: MIT