Entropy Regularization for Mean Field Games with Learning

30 Sep 2020 Xin Guo Renyuan Xu Thaleia Zariphopoulou

Entropy regularization has been extensively adopted to improve the efficiency, the stability, and the convergence of algorithms in reinforcement learning. This paper analyzes both quantitatively and qualitatively the impact of entropy regularization for Mean Field Game (MFG) with learning in a finite time horizon... (read more)

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Entropy Regularization