Single-Agent Reinforcement Learning Surveys

Author: Mhairi Dunion

Date: 2020-10-02

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This blog post contains surveys on single-agent reinforcement learning, listed in reverse chronological order. The focus here is on general reinforcement learning techniques, surveys on specific applications are not included.


  1. A. Lazaridis, A. Fachantidis, I. Vlahavas. Deep Reinforcement Learning: A State-of-the-Art Walkthrough. Journal of Artificial Intelligence Research, vol. 69, pp. 421-1471, 2020.
  2. T.M. Moerland, J. Broekens, C.M. Jonker. Model-based Reinforcement Learning: A Survey. arXiv:2006.16712 [cs.LG], 2020.
  3. E. Puiutta, E.M. Veith. Explainable Reinforcement Learning: A Survey. arXiv:2005.06247 [cs.LG], 2020.
  4. A. Aubret, L. Matignon, S. Hassas. A Survey on Intrinsic Motivation in Reinforcement Learning. arXiv:1908.06976 [cs.LG], 2019.
  5. D.P. Bertsekas. Feature-based Aggregation and Deep Reinforcement Learning: A Survey and Some New Implementations. IEEE/CAA Journal of Automatica Sinica, vol. 6, no. 1, pp. 1-31, 2019.
  6. T.M. Moerland, J. Broekens, C.M. Jonker. Emotion in Reinforcement Learning Agents and Robots: A Survey. Machine Learning, vol. 107, pp. 443–480, 2018.
  7. K. Arulkumaran, M.P. Deisenroth, M. Brundage, A.A. Bharath. Deep Reinforcement Learning: A Brief Survey. IEEE Signal Processing Magazine, vol. 34, no. 6, pp. 26-38, 2017.
  8. A.S. Polydoros, L. Nalpantidis. Survey of Model-Based Reinforcement Learning: Applications on Robotics. Journal of Intelligent and Robotic Systems, vol. 86, pp. 153–173, 2017.
  9. C. Wirth, R. Akrour, G. Neumann, J. Fürnkranz. A Survey of Preference-based Reinforcement Learning Methods. Journal of Machine Learning Research, vol. 18, no. 1, pp. 1-46, 2017.
  10. M. Ghavamzadeh, S. Mannor, J. Pineau, A. Tamar. Bayesian Reinforcement Learning: A Survey. Foundations and Trends in Machine Learning, vol. 8, no. 5-6, pp. 359-492, 2015.
  11. J. Garcia, F. Fernandez. A Comprehensive Survey on Safe Reinforcement Learning. Journal of Machine Learning Research, vol. 16, pp. 1437-1480, 2015.
  12. D. Liu, H. Li, D. Wang. Feature Selection and Feature Learning for High-Dimensional Batch Reinforcement Learning: A Survey. International Journal of Automation and Computing, vol. 12, pp. 229–242, 2015.
  13. J. Kober, J.A. Bagnell, J. Peters. Reinforcement Learning in Robotics: A Survey. The International Journal of Robotics Research, vol. 32, no. 11, pp. 1238–1274, 2013.
  14. I. Grondman, L. Busoniu, G.A.D. Lopes, R. Babuska. A Survey of Actor-Critic Reinforcement Learning: Standard and Natural Policy Gradients. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), vol. 42, no. 6, pp. 1291-1307, 2012.
  15. A. Lazaric. Transfer in Reinforcement Learning: A Framework and a Survey. In: M. Wiering, M. van Otterlo. Reinforcement Learning - State of the Art, vol. 12, Springer, pp. 143-173, 2012.
  16. S. Zhifei, E. Meng Joo. A Survey of Inverse Reinforcement Learning Techniques. International Journal of Intelligent Computing and Cybernetics, vol. 5, no. 3, pp. 293-311, 2012.
  17. M.E. Taylor, P. Stone. Transfer Learning for Reinforcement Learning Domains: A Survey. Journal of Machine Learning Research, vol. 10, pp. 1633-1685, 2009.
  18. A. Gosavi. Reinforcement Learning: A Tutorial Survey and Recent Advances. INFORMS Journal on Computing, vol. 21, no. 2, pp. 178-192, 2009.
  19. M. van Otterlo. A Survey of Reinforcement Learning in Relational Domains. CTIT Technical Report Series, 2005.
  20. L.P. Kaelbling, M.L. Littman, A.W. Moore. Reinforcement Learning: A Survey. Journal of Artificial Intelligence Research, vol. 4, pp. 237-285, 1996.
  21. S.S. Keerthi, B. Ravindran. A Tutorial Survey of Reinforcement Learning. Sadhana, vol. 19, pp. 851-889, 1994.