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cs.LG2023
Regret Lower Bounds in Multi-agent Multi-armed Bandit
Mengfan Xu, Diego Klabjan
Multi-armed Bandit motivates methods with provable upper bounds on regret and also the counterpart lower bounds have been extensively studied in this context. Recently, Multi-agent…
cs.LG2023★ 2 cited
Decentralized Randomly Distributed Multi-agent Multi-armed Bandit with Heterogeneous Rewards
Mengfan Xu, Diego Klabjan
We study a decentralized multi-agent multi-armed bandit problem in which multiple clients are connected by time dependent random graphs provided by an environment. The reward distr…