Web visualisation of the k-armed bandit problem from chapter 2 of Reinforcement Learning: An Introduction.

This is a little React app created using create-react-app. I use Chart.js to draw the charts. The number crunching is done using multiple web workers. I use workerize-loader to load the web worker code without having to eject the React app.

• Deploy to gh-pages branch
  • Using the gh-pages npm package
  • See also GitHub Pages in the 'Deployment' section of the documentation for Create React App
• The main part of the code is vanilla JS/HTML inside a React app. This code needs to be moved into React components.
• Bring in and use react-chartjs-2
• Add UI support for changing settings:
  • Number of web workers (currently 4)
  • Number of bandit arms aka k (currently 10)
  • Number of runs (currently 2000)
  • Number of steps (currently 1000)
• Add UI support for changing experiments:
  • Value of ε for ε-Greedy
  • Value of c for Upper Confidence Bound
  • Setting optimistic initial values
  • etc.
• Add a button to re-run the whole thing
• Add a progress bar during the number crunching

• Reinforcement Learning: An Introduction
• Chart.js
  • "Simple yet flexible JavaScript charting for designers & developers"
• How to use Web Worker with create-react-app
• workerize-loader
  • "A webpack loader that moves a module and its dependencies into a Web Worker, automatically reflecting exported functions as asynchronous proxies"