  This note introduce three Bayesian style Multi-armed bandit algorithms:
Information-directed sampling, Thompson Sampling and Generalized Thompson
Sampling. The goal is to give an intuitive explanation for these three
algorithms and their regret bounds, and provide some derivations that are
omitted in the original papers.
