pavlovjs

Reinforcement learning using Markov Decision Processes


Keywords
learning, markov, decision
License
MIT
Install
npm install pavlovjs@3.1.0

Documentation

Pavlov.js

About

Pavlov.js uses Markov Decision Processes to implement reinforcement learning. It is written in C++ and compiled to JavaScript. For more on reinforcement learning, check out Andrew Ng's notes.

Installation

npm install pavlovjs --save

Compilation

Simply run make. JavaScript code will be in the lib directory.

Example Usage

(we assume that the prize state automatically leads to a trap state which is never left)

var module = require('pavlovjs');

var pavlov = new module.Pavlov();

// transitions and rewards
pavlov.transition({ "state": "A", "action": "R", "state_": "B" });
pavlov.transition({ "state": "B", "action": "B", "state_": "D" });
pavlov.reward(0);

pavlov.transition({ "state": "A", "action": "B", "state_": "C" });
pavlov.transition({ "state": "C", "action": "R", "state_": "D" });
pavlov.transition({ "state": "D", "action": "B", "state_": "D" });
pavlov.transition({ "state": "D", "action": "R", "state_": "D" });
pavlov.reward(0);

pavlov.transition({ "state": "B", "action": "B", "state_": "D" });
pavlov.transition({ "state": "D", "action": "L", "state_": "C" });
pavlov.transition({ "state": "C", "action": "F", "state_": "A" });
pavlov.transition({ "state": "A", "action": "R", "state_": "B" });
pavlov.reward(0);

pavlov.transition({ "state": "C", "action": "R", "state_": "D" });
pavlov.transition({ "state": "D", "action": "F", "state_": "B" });
pavlov.transition({ "state": "B", "action": "L", "state_": "A" });
pavlov.transition({ "state": "A", "action": "L", "state_": "Prize" });
pavlov.reward(0);

pavlov.transition({ "state": "A", "action": "L", "state_": "Prize" });
pavlov.transition({ "state": "Prize", "action": "L", "state_": "Trap" });
pavlov.transition({ "state": "Trap", "action": "B", "state_": "Trap" });
pavlov.reward(1);

// learn from observations
pavlov.learn();

//policy
console.log(pavlov.action('A')); //L
console.log(pavlov.action('B')); //L
console.log(pavlov.action('C')); //F
console.log(pavlov.action('D')); //F

License

The MIT License (MIT)

Copyright (c) 2015 Nathan Epstein

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.