Communication-Efficient Collaborative Regret Minimization in Multi-Armed Bandits

2023/01/26 by Karpov, Nikolai, Zhang, Qin
#FOS: Computer and information sciences #Machine Learning (cs.LG)

paper · doi:10.48550/arxiv.2301.11442

Abstract

In this paper, we study the collaborative learning model, which concerns the tradeoff between parallelism and communication overhead in multi-agent multi-armed bandits. For regret minimization in multi-armed bandits, we present the first set of tradeoffs between the number of rounds of communication among the agents and the regret of the collaborative learning process.

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