Jul 2026
Asymptotically Optimal Regret for Reinforcement Learning without Horizon Dependence
A new bound on total deviation for time-homogeneous MDPs is proved and a cutting bonus that preserves both optimism and the monotonicity needed for planning is designed that preserves both optimism and the monotonicity needed for planning.
Runlong Zhou, Zi-Han Zhang, Maryam Fazel et al.
· arXiv.org · 0 citations