Empirical Evaluation of the Bayesian Learning Automaton Family

Masteroppgave i informasjons- og kommunikasjonsteknologi 2009 – Universitetet i Agder, Grimstad The two-armed bandit problem is a classical optimization problem where a player sequentially selects and pulls one of two arms attached to a gambling machine, and each arm pull results in either a reward or penalty to the player. Each arm is associated with a certain reward probability which is unknown to the player, and the player needs to sequentially select and play an arm and receive a reward or a penalty in order to discover its true reward probability. The overall goal for the player is reward maximization, and the player needs to balance between exploiting existing knowledge or obtaining n…