Variance Reduction for Deep Q-Learning using Stochastic Recursive Gradient

25 Jul 2020 Haonan Jia Xiao Zhang Jun Xu Wei Zeng Hao Jiang Xiaohui Yan Ji-Rong Wen

Deep Q-learning algorithms often suffer from poor gradient estimations with an excessive variance, resulting in unstable training and poor sampling efficiency. Stochastic variance-reduced gradient methods such as SVRG have been applied to reduce the estimation variance (Zhao et al. 2019)... (read more)

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