Multi-Player Bandits: The Adversarial Case

Pragnya Alatur
Pragnya Alatur

Journal of Machine Learning Research, pp. 1-23, 2020.

Cited by: 8|Bibtex|Views26|DOI:https://doi.org/10.3929/ETHZ-B-000414972
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Other Links: dblp.uni-trier.de|arxiv.org|academic.microsoft.com

Abstract:

We consider a setting where multiple players sequentially choose among a common set of actions (arms). Motivated by a cognitive radio networks application, we assume that players incur a loss upon colliding, and that communication between players is not possible. Existing approaches assume that the system is stationary. Yet this assumpt...More

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