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 Jian QIAN


Exploration Bonus for Regret Minimization in Discrete and Continuous Average Reward MDPs

Neural Information Processing Systems

The exploration bonus is an effective approach to manage the explorationexploitation trade-off in Markov Decision Processes (MDPs). While it has been analyzed in infinite-horizon discounted and finite-horizon problems, we focus on designing and analysing the exploration bonus in the more challenging infinitehorizon undiscounted setting.