Control Regularization for Reduced Variance Reinforcement Learning

14 May 2019Richard ChengAbhinav VermaGabor OroszSwarat ChaudhuriYisong YueJoel W. Burdick

Dealing with high variance is a significant challenge in model-free reinforcement learning (RL). Existing methods are unreliable, exhibiting high variance in performance from run to run using different initializations/seeds... (read more)

PDF Abstract

Evaluation results from the paper

  Submit results from this paper to get state-of-the-art GitHub badges and help community compare results to other papers.