Data-Driven Upper Confidence Bounds with Near-Optimal Regret for Heavy-Tailed Bandits

Ambrus Tamás, Szabolcs Szentpéteri, Balázs Csanád Csáji

Stochastic multi-armed bandits (MABs) provide a fundamental reinforcement learning model to study sequential decision making in uncertain environments. The upper confidence bounds…