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Paper · arXiv

Approximating Optimal Policies in Heterogeneous Asynchronous Multi-player Bandits

Motivated by applications to cognitive radio networks, multi-player multi-armed bandits (MMAB) have attracted considerable attention in recent years. The asynchronous variant, in which players are active only at a fraction of timesteps, better reflects real-world decentralized networks, where devices are not permanently active. Despite its practical relevance, this setting remains relatively understudied. Existing work on asynchronous MMAB has focused on homogeneous players, who share the same activation probability, a setting in which the optimal centralized allocation can be easily characterized. In contrast, efficiently computing the optimal allocation in the heterogeneous setting, whe...

AuthorsSacha Arroues-Paykin, Etienne Boursier, Vianney Perchet
Primary categorycs.LG
Published13 October 2026
Last updated at source13 October 2026
cs.LG
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