A One-Armed Bandit Problem with a Concomitant Variable

Michael B. Woodroofe

107 citations0/0 files storedJournal of the American Statistical Association

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Advanced Bandit Algorithms Research Statistical Methods in Clinical Trials Simulation Techniques and Applications

Abstract

We consider a Bayesian sequential allocation problem that incorporates a concomitant variable in the model. Although the model is highly simplified, our results do have some mildly surprising aspects: (a) the approximate solution to the allocation problem is simpler in the presence of concomitant information than in its absence, (b) the exact value of the discount factor is less important than in previous work, and (c) the myopic procedure is asymptotically optimal.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 107 citations exist upstream.

References

1965A Bayes Sequential Sampling Inspection Plan

Cited by

2007Bandits for Taxonomies: A Model-based Approach 2002Randomized Allocation with nonparametric estimation for a multi-armed bandit problem with covariates 2013Ranked bandits in metric spaces: learning diverse rankings over large document collections 2013A Linear Response Bandit Problem 2013A linear response bandit problem 2009Woodroofe’s one-armed bandit problem revisited 1991One-Armed Bandit Problems with Covariates 2017An Actor-Critic Contextual Bandit Algorithm for Personalized Mobile Health Interventions

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.