Abstract
Consider the following problem in sequential design: Two Bernoulli experiments called arm 1 and arm 2 are given with unknown success probabilities. We consider them as random variables with a joint prior distribution μ not concentrated on the boundary of [0, 1]2. The aim is to maximize the expected number of successes in N trials by choosing one of the arms on each trial.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Hengartner, W., D. Kalin and R. Theodorescu (1981). On the Bernoulli Two-Armed Bandit Problem. Math. Operationsforschung Statist., Ser. Optimization 12, 307–316.
Kolonko, M., H. Benzing (1983). On Monotone Optimal Decision Rules and the Stay-on-a-Winner Rule for the Two-Armed Bandit. To appear in Metrika.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1984 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Benzing, H., Kolonko, M. (1984). Monotone Decision Rules for the Two-Armed Bandit. In: Hammer, G., Pallaschke, D. (eds) Selected Topics in Operations Research and Mathematical Economics. Lecture Notes in Economics and Mathematical Systems, vol 226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45567-4_28
Download citation
DOI: https://doi.org/10.1007/978-3-642-45567-4_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-12918-9
Online ISBN: 978-3-642-45567-4
eBook Packages: Springer Book Archive