Arsenii Kuznetsov

Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics

The overestimation bias is one of the major impediments to accurate off-policy learning. This paper investigates a novel way to alleviate the overestimation bias in a continuous control setting. Our method—Truncated Quantile Critics, TQC,—blends three ideas: distributional representation of a critic…