DQN改进的结合

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参考文献

Deep Reinforcement Learning with Double Q-learning, Hado van Hasselt, Arthur Guez, David Silver, 2016 AAAI Conference on Artificial Intelligence (AAAI) DOI: 10.48550/arXiv.1509.06461 - 提出双Q学习算法以减少Q学习中价值高估偏差的原始论文。
Dueling Network Architectures for Deep Reinforcement Learning, Ziyu Wang, Tom Schaul, Matteo Hessel, Hado van Hasselt, Marc Lanctot, Nando de Freitas, 2016 International Conference on Machine Learning (ICML) DOI: 10.48550/arXiv.1511.06581 - 介绍了深度强化学习的Dueling网络架构，分离了状态值和优势函数。
Prioritized Experience Replay, Tom Schaul, John Quan, Ioannis Antonoglou, David Silver, 2016 International Conference on Learning Representations (ICLR) DOI: 10.48550/arXiv.1511.05952 - 介绍了优先经验回放，这是一种根据时间差分误差采样转换的经验回放机制。
Human-level control through deep reinforcement learning, Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, Martin Riedmiller, Andreas K. Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg, Demis Hassabis, 2015 Nature, Vol. 518 DOI: 10.1038/nature14236 - 介绍深度Q网络（DQN）的开创性论文，用于直接从原始像素输入玩Atari游戏。