Multi-agent reinforcement learning (English Wikipedia)

Analysis of information sources in references of the Wikipedia article "Multi-agent reinforcement learning" in English language version.

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  • Li, Tianxu; Zhu, Kun; Luong, Nguyen Cong; Niyato, Dusit; Wu, Qihui; Zhang, Yang; Chen, Bing (2021). "Applications of Multi-Agent Reinforcement Learning in Future Internet: A Comprehensive Survey". arXiv:2110.13484 [cs.AI].
  • Le, Ngan; Rathour, Vidhiwar Singh; Yamazaki, Kashu; Luu, Khoa; Savvides, Marios (2021). "Deep Reinforcement Learning in Computer Vision: A Comprehensive Survey". arXiv:2108.11510 [cs.CV].
  • Moulin-Frier, Clément; Oudeyer, Pierre-Yves (2020). "Multi-Agent Reinforcement Learning as a Computational Tool for Language Evolution Research: Historical Context and Future Challenges". arXiv:2002.08878 [cs.MA].
  • Krishnan, Srivatsan; Jaques, Natasha; Omidshafiei, Shayegan; Zhang, Dan; Gur, Izzeddin; Reddi, Vijay Janapa; Faust, Aleksandra (2022). "Multi-Agent Reinforcement Learning for Microprocessor Design Space Exploration". arXiv:2211.16385 [cs.AR].
  • Li, Yuanzheng; He, Shangyang; Li, Yang; Shi, Yang; Zeng, Zhigang (2023). "Federated Multiagent Deep Reinforcement Learning Approach via Physics-Informed Reward for Multimicrogrid Energy Management". IEEE Transactions on Neural Networks and Learning Systems. PP (5): 5902–5914. arXiv:2301.00641. doi:10.1109/TNNLS.2022.3232630. PMID 37018258. S2CID 255372287.
  • Tuyls, Karl; Omidshafiei, Shayegan; Muller, Paul; Wang, Zhe; Connor, Jerome; Hennes, Daniel; Graham, Ian; Spearman, William; Waskett, Tim; Steele, Dafydd; Luc, Pauline; Recasens, Adria; Galashov, Alexandre; Thornton, Gregory; Elie, Romuald; Sprechmann, Pablo; Moreno, Pol; Cao, Kris; Garnelo, Marta; Dutta, Praneet; Valko, Michal; Heess, Nicolas; Bridgland, Alex; Perolat, Julien; De Vylder, Bart; Eslami, Ali; Rowland, Mark; Jaegle, Andrew; Munos, Remi; Back, Trevor; Ahamed, Razia; Bouton, Simon; Beauguerlange, Nathalie; Broshear, Jackson; Graepel, Thore; Hassabis, Demis (2020). "Game Plan: What AI can do for Football, and What Football can do for AI". arXiv:2011.09192 [cs.AI].
  • Chu, Tianshu; Wang, Jie; Codec├á, Lara; Li, Zhaojian (2019). "Multi-Agent Deep Reinforcement Learning for Large-scale Traffic Signal Control". arXiv:1903.04527 [cs.LG].
  • Belletti, Francois; Haziza, Daniel; Gomes, Gabriel; Bayen, Alexandre M. (2017). "Expert Level control of Ramp Metering based on Multi-task Deep Reinforcement Learning". arXiv:1701.08832 [cs.AI].
  • Ding, Yahao; Yang, Zhaohui; Pham, Quoc-Viet; Zhang, Zhaoyang; Shikh-Bahaei, Mohammad (2023). "Distributed Machine Learning for UAV Swarms: Computing, Sensing, and Semantics". arXiv:2301.00912 [cs.LG].
  • Xu, Lily; Perrault, Andrew; Fang, Fei; Chen, Haipeng; Tambe, Milind (2021). "Robust Reinforcement Learning Under Minimax Regret for Green Security". arXiv:2106.08413 [cs.LG].
  • Leike, Jan; Martic, Miljan; Krakovna, Victoria; Ortega, Pedro A.; Everitt, Tom; Lefrancq, Andrew; Orseau, Laurent; Legg, Shane (2017). "AI Safety Gridworlds". arXiv:1711.09883 [cs.AI].
  • Hadfield-Menell, Dylan; Dragan, Anca; Abbeel, Pieter; Russell, Stuart (2016). "The Off-Switch Game". arXiv:1611.08219 [cs.AI].
  • Hernandez-Leal, Pablo; Kartal, Bilal; Taylor, Matthew E. (2019-11-01). "A survey and critique of multiagent deep reinforcement learning". Autonomous Agents and Multi-Agent Systems. 33 (6): 750–797. arXiv:1810.05587. doi:10.1007/s10458-019-09421-1. ISSN 1573-7454. S2CID 52981002.

doi.org

harvard.edu

ui.adsabs.harvard.edu

marl-book.com

  • Stefano V. Albrecht, Filippos Christianos, Lukas Schäfer. Multi-Agent Reinforcement Learning: Foundations and Modern Approaches. MIT Press, 2024. https://www.marl-book.com/

mlr.press

proceedings.mlr.press

nih.gov

pubmed.ncbi.nlm.nih.gov

openreview.net

science.org

semanticscholar.org

api.semanticscholar.org

stanford.edu

iliad.stanford.edu

utexas.edu

cs.utexas.edu

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