Covariate models for bernoulli bandits
作者:
Murray K. Clayton,
期刊:
Sequential Analysis
(Taylor Available online 1989)
卷期:
Volume 8,
issue 4
页码: 405-426
ISSN:0747-4946
年代: 1989
DOI:10.1080/07474948908836190
出版商: Marcel Dekker, Inc.
关键词: Sequential decisions;one-armed bandits;two-armed bandits;logit;log-linear
数据来源: Taylor
摘要:
Sequential selections are to be made from two stochastic processes, or "arms", each yielding Bernoulli responses. At each stage the arm selected depends on previous observations. The objective is to maximize the expected number of successes in the first n selections. The probability of success for a given selection depends on a covariate through an appropriate transformation. For one arm, this transformation is completely known; for the other, it depends on unknown parameters. Properties of optimal strategies are related to those for non-covariate models. Conditions are described under which it is optimal to observe the arm with unknown parameters if the covariate lies to one side of an index value.
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