Swarm Intelligence Research: From Bio-inspired Single-population Swarm Intelligence to Human-machine Hybrid Swarm Intelligence

群体智能 群体行为 人类智力 人工智能 人口 计算机科学 群机器人 计算智能 粒子群优化 机器学习 社会学 人口学
作者
Guoyin Wang,Dongdong Cheng,Deyou Xia,Hai-Huan Jiang
标识
DOI:10.1007/s11633-022-1367-7
摘要

Swarm intelligence has become a hot research field of artificial intelligence. Considering the importance of swarm intelligence for the future development of artificial intelligence, we discuss and analyze swarm intelligence from a broader and deeper perspective. In a broader sense, we are talking about not only bio-inspired swarm intelligence, but also human-machine hybrid swarm intelligence. In a deeper sense, we discuss the research using a three-layer hierarchy: in the first layer, we divide the research of swarm intelligence into bio-inspired swarm intelligence and human-machine hybrid swarm intelligence; in the second layer, the bio-inspired swarm intelligence is divided into single-population swarm intelligence and multi-population swarm intelligence; and in the third layer, we review single-population, multi-population and human-machine hybrid models from different perspectives. Single-population swarm intelligence is inspired by biological intelligence. To further solve complex optimization problems, researchers have made preliminary explorations in multi-population swarm intelligence. However, it is difficult for bio-inspired swarm intelligence to realize dynamic cognitive intelligent behavior that meets the needs of human cognition. Researchers have introduced human intelligence into computing systems and proposed human-machine hybrid swarm intelligence. In addition to single-population swarm intelligence, we thoroughly review multi-population and human-machine hybrid swarm intelligence in this paper. We also discuss the applications of swarm intelligence in optimization, big data analysis, unmanned systems and other fields. Finally, we discuss future research directions and key issues to be studied in swarm intelligence.
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