Multi-Player Bandits: The Adversarial Case
Journal of Machine Learning Research, pp. 1-23, 2020.
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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