Bayesian Optimization -- Multi-Armed Bandit Problem

TL;DR

This paper surveys Bayesian Optimization techniques for the Multi-Armed Bandit problem, reviewing acquisition functions and portfolio strategies, and replicates experiments to compare results with prior work.

Contribution

It provides a literature survey on Bayesian Optimization methods for multi-armed bandits and includes experimental replication and comparison of existing results.

Findings

Replicated experiments align with original results

Compared different portfolio strategies in Bayesian Optimization

Provided insights into acquisition function effectiveness

Abstract

In this report, we survey Bayesian Optimization methods focussed on the Multi-Armed Bandit Problem. We take the help of the paper "Portfolio Allocation for Bayesian Optimization". We report a small literature survey on the acquisition functions and the types of portfolio strategies used in papers discussing Bayesian Optimization. We also replicate the experiments and report our findings and compare them to the results in the paper. Code link: https://colab.research.google.com/drive/1GZ14klEDoe3dcBeZKo5l8qqrKf_GmBDn?usp=sharing#scrollTo=XgIBau3O45_V.