Intelligent Decision Making Technology and Challenge of Wargame

被引:0
|
作者
Yin Q.-Y. [1 ,2 ]
Zhao M.-J. [1 ]
Ni W.-C. [1 ,2 ]
Zhang J.-G. [1 ,2 ]
Huang K.-Q. [1 ]
机构
[1] Institute of Automation, Chinese Academy of Sciences, Beijing
[2] University of Chinese Academy of Sciences, Beijing
来源
基金
中国国家自然科学基金;
关键词
game learning; human-machine confrontation; intelligent decision making technology; Wargame;
D O I
10.16383/j.aas.c210547
中图分类号
学科分类号
摘要
In recent years, decision-making intelligence based on human-machine confrontation has achieved rapid development. For example, artificial intelligence (AI) technology such as AlphaGo and AlphaStar have defeated top human players in games Go and StarCraft, respectively. Nowadays, wargame, as a new verification environment for human-machine confrontation, attracts more and more researchers due to new challenges being raised, i.e., asymmetric environmental decision-making and randomness with high-risk decision-making. In this paper, we will sort out the differences between wargame and the current mainstream human-machine confrontation environments such as Go, Poker and StarCraft. Then, we explain the development status of wargame intelligent technology, and analyze the limitations of current mainstream technologies. Finally, we present our thoughts about future development of technologies for wargame, hoping to inspire researchers for through study on wargame. © 2023 Science Press. All rights reserved.
引用
收藏
页码:913 / 928
页数:15
相关论文
共 50 条
  • [31] Intelligent multi-objective decision-making model with RFID technology for production planning
    Wong, W. K.
    Guo, Z. X.
    Leung, S. Y. S.
    [J]. INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2014, 147 : 647 - 658
  • [32] Consensus-based intelligent group decision-making model for the selection of advanced technology
    Choudhury, A. K.
    Shankar, Ravi
    Tiwari, M. K.
    [J]. DECISION SUPPORT SYSTEMS, 2006, 42 (03) : 1776 - 1799
  • [33] Platform for intelligent decision-making support system was developed in National University of Defence Technology
    Cheng, Fang
    [J]. Gaojishu Tongxin/High Technology Letters, 1995, 5 (12):
  • [34] INTELLIGENT AUTOMATIC DECISION-MAKING SYSTEM
    KRINITSKII, NA
    FEDOTOVA, DE
    KRINITSKII, VN
    [J]. PROGRAMMING AND COMPUTER SOFTWARE, 1992, 18 (06) : 247 - 254
  • [35] Intelligent multi-attribute decision making
    [J]. Binggong Xuebao, 1 (90-93):
  • [36] Intelligent decision making using soft computing
    Yager, Ronald R.
    [J]. PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS AND KNOWLEDGE ENGINEERING (ISKE 2007), 2007,
  • [37] Intelligent decision making for service and manufacturing industries
    Junwei Wang
    Su Xiu Xu
    Gangyan Xu
    [J]. Journal of Intelligent Manufacturing, 2020, 31 : 2089 - 2090
  • [38] Applications of intelligent multiobjective fuzzy decision making
    Ruspini, EH
    [J]. COMPUTATIONAL INTELLIGENCE: SOFT COMPUTING AND FUZZY-NEURO INTEGRATION WITH APPLICATIONS, 1998, 162 : 514 - 520
  • [39] Intelligent decision making for service and manufacturing industries
    Wang, Junwei
    Xu, Su Xiu
    Xu, Gangyan
    [J]. JOURNAL OF INTELLIGENT MANUFACTURING, 2020, 31 (08) : 2089 - 2090
  • [40] Intelligent sensing and decision making in smart technologies
    Zhao, Wenbing
    Wu, Jinsong
    Shi, Peng
    Wang, Hongqiao
    [J]. INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS, 2018, 14 (11):