A Boosting-based Deep Neural Networks Algorithm for Reinforcement Learning

摘要

In this paper, a new boosting-based deep neural networks algorithm is designed for improving the performance of model-free reinforcement learning structures. Based on theoretical proof and performance analysis, it is going to demonstrate that the new approach gives a faster convergence speed and a better return compared to existing deep neural network based RL approaches, like deep