bayesian-bandit v0.10.0

#bayesian-bandit.js

This is an adaptation of the Bayesian Bandit code from Probabilistic Programming and Bayesian Methods for Hackers, specifically d3bandits.js.

The code has been rewritten to be more idiomatic and also usable as a browser script or npm package. Additionally, unit tests are included.

#Quick Start

From node.js:

npm install bayesian-bandit
node

Then:

var Bandit = require('bayesian-bandit').Bandit

In the browser:

<script src="https://raw.github.com/omphalos/bayesian-bandit.js/master/bayesian-bandit.js"></script>

Sample JavaScript:

var bandit = new Bandit({ numberOfArms: 2 })

bandit.arms[0].reward(0) // Arm 0 loses once.
bandit.arms[0].reward(1) // Arm 0 wins once.

bandit.arms[1].reward(0) // Arm 1 loses once.
bandit.arms[1].reward(1) // Arm 1 wins once.
bandit.arms[1].reward(1) // Arm 1 wins twice.

bandit.selectArm() // Arm 1 is more likely, so this probably returns 1

If you have pre-existing data that you want to load, you can explicitly pass in data via constructor. The following creates a bandit with 3 arms

var bandit = new Bandit({
    arms: [{ count: 10, sum: 2 },
            { count: 20, sum: 10 },
            { count: 15: sum: 1}]
})

You can also take advantage of the rewardMultiple function on the arms:

var bandit = new Bandit({ numberOfArms: 3 })

bandit.arms[0].rewardMultiple(10, 2)  // Arm 0 wins 2 of 10 times
bandit.arms[1].rewardMultiple(20, 10) // Arm 1 wins 10 of 20 times 
bandit.arms[2].rewardMultiple(15, 1)  // Arm 2 wins 1 of 15 times

#Unit Tests

The unit tests use nodeunit, which should get installed with:

npm install

Then you can run unit tests with:

npm test