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cs.LG2026
Robust Multi-Agent Bandits with Heavy-Tailed Rewards and Information Asymmetry
Daphne Feng, Ricardo Parada, Lily Jiang +2
The multi-armed bandit problem is a central framework in sequential decision-making, extensively studied under sub-Gaussian reward assumptions. However, real-world applications oft…
cs.LG2026
Coordinating the Unknown Lipschitz Constant in Multiplayer Bandits
Ricardo Parada, Chenzhang Zhao, William Chang
Motivated by decentralized applications, we study cooperative multi-agent bandits in continuous (Lipschitz) action spaces when the Lipschitz constant is unknown. We consider three…