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- W2912498753 abstract "We study distributed cooperative decision-making in a multi-agent stochastic multi-armed bandit (MAB) problem in which agents are connected through an undirected graph and observe the actions and rewards of their neighbors. We develop a novel policy based on partitions of the communication graph and propose a distributed method for selecting an arbitrary number of leaders and partitions. We analyze this new policy and evaluate its performance using Monte-Carlo simulations." @default.
- W2912498753 created "2019-02-21" @default.
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- W2912498753 date "2018-12-01" @default.
- W2912498753 modified "2023-10-17" @default.
- W2912498753 title "Social Imitation in Cooperative Multiarmed Bandits: Partition-Based Algorithms with Strictly Local Information" @default.
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- W2912498753 doi "https://doi.org/10.1109/cdc.2018.8619744" @default.
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