Sign-Separated Asymmetric Finite-Time Error Analysis of Q-Learning

Donghwan Lee

Q-learning is known to suffer from overestimation bias: because the Bellman update maximizes noisy or imperfect action-value estimates, positive errors can be selected and propagat…