博弈的存在与实践：对多智能体博弈发展的思考

董琦; 吴镇宇; 陆军; 孙凤松; 王锦宇; 杨焱煜; 尚晓舟

doi:10.1631/FITEE.2100593

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博弈的存在与实践：对多智能体博弈发展的思考

多智能体系统的体系化和组织化博弈专题 | Updated：2022-09-08

- 博弈的存在与实践：对多智能体博弈发展的思考
- Existence and practice of gaming: thoughts on the development of multi-agent system gaming
- 信息与电子工程前沿（英文） 2022年23卷第7期页码：995-1001
- Affiliations：
  
  1.China Academy of Electronics and Information Technology, Beijing100049, China
  2.School of Information and Electronics, Beijing Institute of Technology, Beijing100081, China
  3.School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing100876, China
- Author bio：
  
  E-mail: dongqiouc@126.com;
  E-mail: zhenyuwu1993@126.com;
  ‡Corresponding authors
- Funds：
  
  National Natural Science Foundation of China(61803353)
- DOI：10.1631/FITEE.2100593
  中图分类号：
- 纸质出版日期：2022-07-23，
  
  收稿日期：2021-12-30，
  
  录用日期：2022-05-05
- Accepted：
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董琦, 吴镇宇, 陆军, 等. 博弈的存在与实践：对多智能体博弈发展的思考[J]. 信息与电子工程前沿（英文）, 2022,23(7):995-1001.

QI DONG, ZHENYU WU, JUN LU, et al. Existence and practice of gaming: thoughts on the development of multi-agent system gaming. [J]. Frontiers of information technology & electronic engineering, 2022, 23(7): 995-1001.
董琦, 吴镇宇, 陆军, 等. 博弈的存在与实践：对多智能体博弈发展的思考[J]. 信息与电子工程前沿（英文）, 2022,23(7):995-1001. DOI： 10.1631/FITEE.2100593.

QI DONG, ZHENYU WU, JUN LU, et al. Existence and practice of gaming: thoughts on the development of multi-agent system gaming. [J]. Frontiers of information technology & electronic engineering, 2022, 23(7): 995-1001. DOI： 10.1631/FITEE.2100593.

摘要

博弈是宇宙中的一种普遍存在。本文从人类对博弈的认识过程出发，探讨了博弈的存在与实践，阐述了多智能体博弈研究难点，并基于演化思想，从系统论的角度出发，提出多智能体演化博弈理论框架。以下一代预警探测系统为例，介绍了多智能体演化博弈的应用实践。构建了多智能体自组织博弈决策模型和多智能体强化学习方法，对研究高维复杂环境下的组织化、体系化博弈行为具有重要意义。

Abstract

Game is a universal being in the universe. Starting with human understanding of the game process

we discuss the existence and practice of gaming

expound challenges in multi-agent gaming

and put forward a theoretical framework for a multi-agent evolutionary game based on the idea of evolution and system theory. Taking the next-generation early warning and detection system as an example

we introduce the applications of multi-agent evolutionary game. We construct a multi-agent self-organizing game decision-making model and develop a multi-agent method based on reinforcement learning

which are significant in studying organized and systematic game behaviors in a high-dimensional complex environment.

关键词

博弈多智能体系统多智能体演化博弈预警探测

Keywords

references

Abu Turab Rizvi S, 2007. Aumann's and Schelling's game theory: the Nobel Prize in Economic Science, 2005. Rev Polit Econ, 19(3):297-316. doi: 10.1080/09538250701452990http://doi.org/10.1080/09538250701452990

Alsheikh MA, Hoang DT, Niyato D, et al., 2015. Markov decision processes with applications in wireless sensor networks: a survey. IEEE Commun Surv Tutor, 17(3):1239-1267. doi: 10.1109/COMST.2015.2420686http://doi.org/10.1109/COMST.2015.2420686

Archetti M, Pienta KJ, 2019. Cooperation among cancer cells: applying game theory to cancer. Nat Rev Cancer, 19(2):110-117. doi: 10.1038/s41568-018-0083-7http://doi.org/10.1038/s41568-018-0083-7

Cavagna A, Cimarelli A, Giardina I, et al., 2010. Scale-free correlations in starling flocks. Proc Nat Acad Sci USA, 107(26):11865-11870. doi: 10.1073/pnas.1005766107http://doi.org/10.1073/pnas.1005766107

Gupta A, Savarese S, Ganguli S, et al., 2021. Embodied intelligence via learning and evolution. Nat Commun, 12(1):5721. doi: 10.1038/s41467-021-25874-zhttp://doi.org/10.1038/s41467-021-25874-z

Hayat S, Yanmaz E, Muzaffar R, 2016. Survey on unmanned aerial vehicle networks for civil applications: a communications viewpoint. IEEE Commun Surv Tutor, 18(4):2624-2661. doi: 10.1109/COMST.2016.2560343http://doi.org/10.1109/COMST.2016.2560343

Heidegger M, 2013. Sein und Zeit. De Gruyter, Germany(in German).

Heidegger M, Mörchen H, 1988. Vom Wesen der Wahrheit Zu Platons Höhlengleichnis und Theätet. V. Klostermann, Frankfurt, USA(in German).

Hilbe C, Šimsa Š, Chatterjee K, et al., 2018. Evolution of cooperation in stochastic games. Nature, 559(7713):246-249. doi: 10.1038/s41586-018-0277-xhttp://doi.org/10.1038/s41586-018-0277-x

Kant I, 2020. Kritik der Reinen Vernunft. BoD–Books on Demand, Germany(in German).

Li L, Wang X, Wang KF, et al., 2019. Parallel testing of vehicle intelligence via virtual-real interaction. Sci Robot, 4(28):eaaw4106. doi: 10.1126/scirobotics.aaw4106http://doi.org/10.1126/scirobotics.aaw4106

Liu M, Lu J, 2015. Overview of AEW character and development trend. J China Acad Electron Inform Technol, 10(3):278-282(in Chinese).

Liu ZA, Nishi T, 2022. Strategy dynamics particle swarm optimizer. Inform Sci, 582:665-703. doi: 10.1016/j.ins.2021.10.028http://doi.org/10.1016/j.ins.2021.10.028

Lu J, Shan BN, 2020. Information system development thinking. J Electr Electron Edu, 42:1(in Chinese).

JrNash JF, 1950. Equilibrium points in n-person games. Proc Nat Acad Sci USA, 36(1):48-49. doi: 10.1073/pnas.36.1.48http://doi.org/10.1073/pnas.36.1.48

Nowak MA, 2006. Five rules for the evolution of cooperation. Science, 314(5805):1560-1563. doi: 10.1126/science.1133755http://doi.org/10.1126/science.1133755

Omidshafiei S, Papadimitriou C, Piliouras G, et al., 2019. a-Rank: multi-agent evaluation by evolution. Sci Rep, 9(1):9937. doi: 10.1038/s41598-019-45619-9http://doi.org/10.1038/s41598-019-45619-9

Shao K, Zhu YH, Zhao DB, 2019. Starcraft micromanagement with reinforcement learning and curriculum transfer learning. IEEE Trans Emerg Top Comput Intell, 3(1):73-84. doi: 10.1109/TETCI.2018.2823329http://doi.org/10.1109/TETCI.2018.2823329

Shoham Y, Leyton-Brown K, 2008. Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations. Cambridge University Press, Cambridge, UK.doi: 10.1017/CBO9780511811654http://doi.org/10.1017/CBO9780511811654

Silver D, Huang A, Maddison CJ, et al., 2016. Mastering the game of Go with deep neural networks and tree search. Nature, 529(7587):484-489. doi: 10.1038/nature16961http://doi.org/10.1038/nature16961

Smith JM, 1982. Evolution and the Theory of Games. Cambridge University Press, Cambridge, UK.doi: 10.1017/CBO9780511806292http://doi.org/10.1017/CBO9780511806292

Von Neumann J, 1928. Zur theorie der gesellschaftsspiele. Math Ann, 100(1):295-320(in German).

Von Neumann J, Morgenstern O, 2007. Theory of Games and Economic Behavior. Princeton University Press, Princeton, USA.

Wang MY, Li YM, Cheng ZX, et al., 2021. Evolution and equilibrium of a green technological innovation system: simulation of a tripartite game model. J Clean Prod, 278:123944. doi: 10.1016/j.jclepro.2020.123944http://doi.org/10.1016/j.jclepro.2020.123944

Xu GZ, 2000. Systems Science and Engineering. Shanghai Scientific Technologically Education Publishing House, Shanghai, China(in Chinese).

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