Multi-Agent Reinforcement Learning Surveys

Author: Ibrahim Ahmed

Date: 2020-10-27

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

Surveys

  1. S. Pateria, B. Subagdja, A. Tan, C. Quek. Hierarchical Reinforcement Learning: A Comprehensive Survey. ACM Computing Surveys, Volume 54, Issue 5, 2021. [includes section on HRL for MARL]
  2. S. Gronauer, K. Diepold. Multi-Agent Deep Reinforcement Learning: A Survey. Artificial Intelligence Review, 2021.
  3. C. Moulin-Frier, P. Oudeyer. Multi-Agent Reinforcement Learning as a Computational Tool for Language Evolution Research: Historical Context and Future Challenges. arXiv:2002.08878 [cs.MA], 2020.
  4. M. Zaïem, E. Bennequin. Learning to Communicate in Multi-Agent Reinforcement Learning: A Review. arXiv:1911.05438 [cs.LG], 2019.
  5. P. Hernandez-Leal, B. Kartal, M. E. Taylor. A Survey and Critique of Multiagent Deep Reinforcement Learning. Autonomous Agents and Multi-Agent Systems, vol. 33, no. 6, pp. 1-48, 2019.
  6. R. Rădulescu, P. K. Mannion, D. M. Roijers, A. Nowé. Multi-Objective Multi-Agent Decision Making: A Utility-based Analysis and Survey. arXiv:1909.02964 [cs.MA], 2019.
  7. G. Papoudakis, F. Christianos, A. Rahman, S.V. Albrecht. Dealing with Non-Stationarity in Multi-Agent Deep Reinforcement Learning. arXiv:1906.04737 [cs.LG], 2019.
  8. F. Silva, A. Costa. A Survey on Transfer Learning for Multiagent Reinforcement Learning Systems. Journal of Artificial Intelligence Research, vol. 64, pp. 645-703, 2019.
  9. T. T. Nguyen, N. D. Nguyen, S. Nahavandi. Deep Reinforcement Learning for Multi-Agent Systems: A Review of Challenges, Solutions and Applications. arXiv:1812.11794 [cs.LG], 2019.
  10. S.V. Albrecht, P. Stone. Autonomous Agents Modelling Other Agents: A Comprehensive Survey and Open Problems. arXiv:1709.08071 [cs.AI], 2018.
  11. K. Tuyls, P. Stone. Multiagent Learning Paradigms. Lecture Notes in Artificial Intelligence, vol. 10767, pp. 3-21, 2018.
  12. P. Hernandez-Leal, M. Kaisers, T. Baarslag, E. M. De Cote. A Survey of Learning in Multiagent Environments: Dealing with Non-Stationarity. arXiv:1707.09183 [cs.MA], 2017.
  13. D. Bloembergen, K. Tuyls, D. Hennes, M. Kaisers. Evolutionary Dynamics of Multi-agent Learning: A Survey. Journal Of Artificial Intelligence Research, vol. 53, no. 1, pp. 659-97, 2015.
  14. K. Tuyls, G. Weiss. Multiagent Learning: Basics, Challenges, and Prospects. AI Magazine, vol. 33, no. 3, pp. 41-52, 2012.
  15. L. Matignon, G. J. Laurent, N. Le Fort-piat. Independent Reinforcement Learners in Cooperative Markov Games: A Survey Regarding Coordination Problems. The Knowledge Engineering Review, vol. 27, no. 1, pp. 1-31, 2012.
  16. A. Nowé, P. Vrancx, Y. De Hauwere. Game Theory and Multi-agent Reinforcement Learning. Reinforcement Learning State-of-the-Art, pp. 441-470, 2012.
  17. L. Buşoniu, R. Babuška, B. De Schutter. Multi-agent Reinforcement Learning: An Overview. Studies in Computational Intelligence, vol. 310, pp. 183-221, 2010.
  18. A. V. Bab, R. I. Brafman. Multi-Agent Reinforcement Learning in Common Interest and Fixed Sum Stochastic Games: An Experimental Study. Journal of Machine Learning Research, vol. 9, pp. 2635-2675, 2008.
  19. L. Busoniu, R. Babuska, B. De Schutte. A Comprehensive Survey of Multiagent Reinforcement Learning. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), vol. 38, pp. 156-172, 2008.
  20. Y. Shoham, R. Powers, T. Grenager. If Multi-Agent Learning is the Answer, What is the Question?. Artificial Intelligence, vol. 171, no. 7, pp. 365-377, 2007.
  21. L. Panait, S. Luke. Cooperative Multi-Agent Learning: The State of the Art. Autonomous Agents and Multi-Agent Systems, vol. 11, no. 3, pp. 387-434, 2005.
  22. P. J. Hoen, K. Tuyls, L. Panait, S. Luke. An Overview of Cooperative and Competitive Multiagent Learning. Proceedings of the First International Workshop on Learning and Adaption in Multi-Agent Systems, 2005.
  23. E. Yang, D. Gu. Multiagent Reinforcement Learning for Multi-Robot Systems: A Survey. 2004.
  24. Y. Shoham, R. Powers, T. Grenager. Multi-Agent Reinforcement Learning: A Critical Survey. 2003.
  25. E. Alonso, M. D'inverno, D. Kudenko, M. Luck, J. Noble. Learning in Multi-agent Systems. The Knowledge Engineering Review, vol. 16, no. 3, 2001.
  26. P. Stone, M. Veloso. Multiagent Systems: A Survey from a Machine Learning Perspective. Autonomous Robots, vol. 8, no. 3, 2000.
  27. S. Sen, G. Weiss. Learning in Multiagent Systems. Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence, pp. 259-298, 1999.