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- W3159294092 abstract "In this article, we study stochastic multiarmed bandits with many players. The players do not know the number of players, cannot communicate with each other, and if multiple players select a common arm, they collide and none of them receive any reward. We consider the static scenario, where the number of players remains fixed, and the dynamic scenario, where the players enter and leave at any time. We provide algorithms based on a novel “trekking approach” that guarantees constant regret for the static case and sublinear regret for the dynamic case with high probability. The trekking approach eliminates the need to estimate the number of players resulting in fewer collisions and improved regret performance compared to state-of-the-art algorithms. We also develop an epoch-less algorithm that eliminates any requirement of time synchronization across the players provided each player can detect the presence of other players on an arm. We validate our theoretical guarantees using simulation-based and real testbed-based experiments." @default.
- W3159294092 created "2021-05-10" @default.
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- W3159294092 date "2022-05-01" @default.
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- W3159294092 title "Multiplayer Bandits: A Trekking Approach" @default.
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- W3159294092 doi "https://doi.org/10.1109/tac.2021.3077454" @default.
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