On the k-armed Bernoulli bandit: monotonicity of the total reward under an arbitrary prior distribution
作者:
Harald Benzing,
Karl Hinderer,
Michael Kolonko,
期刊:
Mathematische Operationsforschung und Statistik. Series Optimization
(Taylor Available online 1984)
卷期:
Volume 15,
issue 4
页码: 583-595
ISSN:0323-3898
年代: 1984
DOI:10.1080/02331938408842974
出版商: Akademic-Verlag
数据来源: Taylor
摘要:
We investigate monotonicity properties of the success probabilities and the total reward when the number of previously observed successes and failures change. Using a well-known Bayesian approach and dynamic programming we give conditions in terms of the covariances of the posterior distributions and in terms of the support of the prior distribution. Special order relations for the number of successes and failures allow a simple and unified treatment of different cases. The results extend some of the investigations of Hengartner/Kalin/Theodorescu [1].
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