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cs.LG2025
Decentralized Asynchronous Multi-player Bandits
Jingqi Fan, Canzhe Zhao, Shuai Li +1
In recent years, multi-player multi-armed bandits (MP-MAB) have been extensively studied due to their wide applications in cognitive radio networks and Internet of Things systems.…
cs.LG2025
Learning with Limited Shared Information in Multi-agent Multi-armed Bandit
Junning Shao, Siwei Wang, Zhixuan Fang
Multi-agent multi-armed bandit (MAMAB) is a classic collaborative learning model and has gained much attention in recent years. However, existing studies do not consider the case w…
cs.LG2025
Efficient and Optimal Policy Gradient Algorithm for Corrupted Multi-armed Bandits
Jiayuan Liu, Siwei Wang, Zhixuan Fang
In this paper, we consider the stochastic multi-armed bandits problem with adversarial corruptions, where the random rewards of the arms are partially modified by an adversary to f…