6533b85cfe1ef96bd12bc7cb
RESEARCH PRODUCT
The Bayesian Learning Automaton — Empirical Evaluation with Two-Armed Bernoulli Bandit Problems
Ole-christoffer Granmosubject
Balance (metaphysics)Optimization problemWake-sleep algorithmbusiness.industryBayesian inferenceMachine learningcomputer.software_genreAutomatonBernoulli's principleArtificial intelligencebusinessBeta distributioncomputerMathematicsdescription
The two-armed Bernoulli bandit (TABB) problem is a classical optimization problem where an agent sequentially pulls one of two arms attached to a gambling machine, with each pull resulting either in a reward or a penalty. The reward probabilities of each arm are unknown, and thus one must balance between exploiting existing knowledge about the arms, and obtaining new information.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2009-01-01 |