A survey of the pursuit-evasion problem in swarm intelligence

被引:8
|
作者
Mu, Zhenxin [1 ,2 ]
Pan, Jie [1 ]
Zhou, Ziye [1 ]
Yu, Junzhi [1 ]
Cao, Lu [2 ]
机构
[1] Peking Univ, Coll Engn, Dept Adv Mfg & Robot, State Key Lab Turbulence & Complex Syst, Beijing 100871, Peoples R China
[2] Natl Innovat Inst Def Technol, Beijing 100071, Peoples R China
基金
中国国家自然科学基金;
关键词
Swarm behavior; Pursuit-evasion; Artificial systems; Biological model; Collective motion; COORDINATED COLLECTIVE MOTION; MULTIAGENT SYSTEMS; CONSENSUS PROBLEMS; ANIMAL GROUPS; STRATEGIES; GAMES; AGENTS; COOPERATION; ALGORITHMS; FLOCKING;
D O I
10.1631/FITEE.2200590
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
For complex functions to emerge in artificial systems, it is important to understand the intrinsic mechanisms of biological swarm behaviors in nature. In this paper, we present a comprehensive survey of pursuit-evasion, which is a critical problem in biological groups. First, we review the problem of pursuit-evasion from three different perspectives: game theory, control theory and artificial intelligence, and bio-inspired perspectives. Then we provide an overview of the research on pursuit-evasion problems in biological systems and artificial systems. We summarize predator pursuit behavior and prey evasion behavior as predator-prey behavior. Next, we analyze the application of pursuit-evasion in artificial systems from three perspectives, i.e., strong pursuer group vs. weak evader group, weak pursuer group vs. strong evader group, and equal-ability group. Finally, relevant prospects for future pursuit-evasion challenges are discussed. This survey provides new insights into the design of multi-agent and multi-robot systems to complete complex hunting tasks in uncertain dynamic scenarios.
引用
收藏
页码:1093 / 1116
页数:24
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