bayesian-bandits
v0.1.2
Published
Bayesian Bandits in JavaScipt
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3
Readme
Bayesian Bandits
References:
- https://web.stanford.edu/~bvr/pubs/TS_Tutorial.pdf
- https://towardsdatascience.com/thompson-sampling-fc28817eacb8
Quick Start:
In the root of your folder run yarn add bayesian-bandits
to install the package.
Inside your JS/TS files:
// Example to help Megan choose what chocolate to buy for maximum enjoyment
// without making it completely impossible for tastes to change
import { chooseArm, rewardArm, bernoulli } from 'bayesian-bandits';
const candies = {
arms: [
{
attempts: 20,
sum: 10,
name: 'Twix',
},
{
attempts: 20,
sum: 18,
name: 'Recees',
},
{
attempts: 20,
sum: 14,
name: 'Top Deck',
},
{
attempts: 20,
sum: 1,
name: 'Mounds',
},
],
};
// To choose the arm you want to pull
const armIndex = chooseArm(banditState.arms);
// Deremine the reward for the arm based on your application logic
const armReward = 1;
// Number of total attemts that resulted in the above reward
const armReward = 1;
const updatedBanditArms = rewardArm(
candies.arms,
armIndex,
armReward,
attempts
);
// Store the updated Bandit Arms in state ready for reuse later on.
storeSomethingMethod(updatedBandits);
License
MIT