#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:
">
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
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