A Theory of Regularized Markov Decision Processes

Matthieu Geist, Bruno Scherrer, Olivier Pietquin

Abstract: Many recent successful (deep) reinforcement learning algorithms make use of regularization, generally based on entropy or Kullback-Leibler divergence. We propose a general theory of regularized Mar...