Existence and practice of gaming: thoughts on the development of multi-agent system gaming

Qi DONG; Zhenyu WU; Jun LU; Fengsong SUN; Jinyu WANG; Yanyu YANG; Xiaozhou SHANG

doi:10.1631/FITEE.2100593

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Existence and practice of gaming: thoughts on the development of multi-agent system gaming

Special Feature on Institutionalized and Systematized Gaming (InSys Gaming) for Multi-agent Systems | Updated：2022-09-08

- Existence and practice of gaming: thoughts on the development of multi-agent system gaming
- 博弈的存在与实践：对多智能体博弈发展的思考
- Frontiers of Information Technology & Electronic Engineering Vol. 23, Issue 7, Pages: 995-1001(2022)
- 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：
- DOI：10.1631/FITEE.2100593
  CLC：
- Received：30 December 2021，
  
  Accepted：05 May 2022，
  
  Published：23 July 2022
- Accepted：
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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：

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.

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