Single-Agent Reinforcement Learning Surveys

Author: Mhairi Dunion

Date: 2020-10-02

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

Surveys

[1] T.M. Moerland, J. Broekens, C.M. Jonker. Model-based Reinforcement Learning: A Survey. arXiv:2006.16712 [cs.LG], 2020.

[2] E. Puiutta, E.M. Veith. Explainable Reinforcement Learning: A Survey. arXiv:2005.06247 [cs.LG], 2020.

[3] A. Aubret, L. Matignon, S. Hassas. A Survey on Intrinsic Motivation in Reinforcement Learning. arXiv:1908.06976 [cs.LG], 2019.

[4] 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.

[5] 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.

[6] 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.

[7] 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.

[8] 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.

[9] 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.

[10] J. Garcia, F. Fernandez. A Comprehensive Survey on Safe Reinforcement Learning. Journal of Machine Learning Research, vol. 16, pp. 1437-1480, 2015.

[11] 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.

[12] 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.

[13] 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.

[14] 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.

[15] 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.

[16] M.E. Taylor, P. Stone. Transfer Learning for Reinforcement Learning Domains: A Survey. Journal of Machine Learning Research, vol. 10, pp. 1633-1685, 2009.

[17] A. Gosavi. Reinforcement Learning: A Tutorial Survey and Recent Advances. INFORMS Journal on Computing, vol. 21, no. 2, pp. 178-192, 2009.

[18] M. van Otterlo. A Survey of Reinforcement Learning in Relational Domains. CTIT Technical Report Series, 2005.

[19] L.P. Kaelbling, M.L. Littman, A.W. Moore. Reinforcement Learning: A Survey. Journal of Artificial Intelligence Research, vol. 4, pp. 237-285, 1996.

[20] S.S. Keerthi, B. Ravindran. A Tutorial Survey of Reinforcement Learning. Sadhana, vol. 19, pp. 851-889, 1994.