One-Armed Bandit Problems with Covariates
Sarkar, Jyotirmoy
Ann. Statist., Tome 19 (1991) no. 1, p. 1978-2002 / Harvested from Project Euclid
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As does Woodroofe, we consider a Bayesian sequential allocation between two treatments that incorporates a covariate. The goal is to maximize the total discounted expected reward from an infinite population of patients. Although our model is more general than Woodroofe's, we are able to duplicate his main result: The myopic rule is asymptotically optimal.
Publié le : 1991-12-14
Classification:  Sequential allocation,  one-armed bandit problem,  Bayesian analysis,  regret,  myopic policy,  asymptotically optimal,  62L10 
@article{1176348382,
     author = {Sarkar, Jyotirmoy},
     title = {One-Armed Bandit Problems with Covariates},
     journal = {Ann. Statist.},
     volume = {19},
     number = {1},
     year = {1991},
     pages = { 1978-2002},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1176348382}
}

Sarkar, Jyotirmoy. One-Armed Bandit Problems with Covariates. Ann. Statist., Tome 19 (1991) no. 1, pp.  1978-2002. http://gdmltest.u-ga.fr/item/1176348382/