We make a survey about the survey of DRL, ranking with the publishing time as:
1. Tai, L., Zhang, J., Liu, M., Boedecker, J., & Burgard, W. (2016). A survey of deep network solutions for learning control in robotics: From reinforcement to imitation. arXiv preprint arXiv:1612.07139.
2. Mousavi, S. S., Schukat, M., & Howley, E. (2016, September). Deep reinforcement learning: an overview. In Proceedings of SAI Intelligent Systems Conference (pp. 426-440). Springer, Cham.
3. Gu, S., Holly, E., Lillicrap, T., & Levine, S. (2017, May). Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates. In 2017 IEEE international conference on robotics and automation (ICRA) (pp. 3389-3396). IEEE.
4. Arulkumaran, K., Deisenroth, M. P., Brundage, M., & Bharath, A. A. (2017). Deep reinforcement learning: A brief survey. IEEE Signal Processing Magazine, 34(6), 26-38.
5. Li, Y. (2017). Deep reinforcement learning: An overview. arXiv preprint arXiv:1701.07274.
6. Christiano, P. F., Leike, J., Brown, T., Martic, M., Legg, S., & Amodei, D. (2017). Deep reinforcement learning from human preferences. In Advances in Neural Information Processing Systems (pp. 4299-4307).
7. Nguyen, N. D., Nguyen, T., & Nahavandi, S. (2017). System design perspective for human-level agents using deep reinforcement learning: A survey. IEEE Access, 5, 27091-27102.
8. Agostinelli, F., Hocquet, G., Singh, S., & Baldi, P. (2018). From Reinforcement Learning to Deep Reinforcement Learning: An Overview. In Braverman Readings in Machine Learning. Key Ideas from Inception to Current State (pp. 298-328). Springer, Cham.
9. Hernandez-Leal, P., Kartal, B., & Taylor, M. E. (2019). A survey and critique of multiagent deep reinforcement learning. Autonomous Agents and Multi-Agent Systems, 33(6), 750-797.
10. Alom, M. Z., Taha, T. M., Yakopcic, C., Westberg, S., Sidike, P., Nasrin, M. S., … & Asari, V. K. (2019). A state-of-the-art survey on deep learning theory and architectures. Electronics, 8(3), 292.
11. Li, G., Gomez, R., Nakamura, K., & He, B. (2019). Human-Centered Reinforcement Learning: A Survey. IEEE Transactions on Human-Machine Systems, 49(4), 337-349