TY - JOUR
T1 - Swarm intelligence
T2 - A survey of model classification and applications
AU - WANG, Chao
AU - ZHANG, Shuyuan
AU - MA, Tianhang
AU - XIAO, Yuetong
AU - CHEN, Michael Zhiqiang
AU - WANG, Lei
N1 - Publisher Copyright:
© 2024
PY - 2025/3
Y1 - 2025/3
N2 - Swarm Intelligence (SI) is a collective behavior that emerges from interaction between individuals in a group. Typical SI includes fish schooling, ant foraging, bird migration, and so on. A great deal of models have been introduced to characterize the mechanism of SI. This article reviews several typical models and classifies them into four categories: self-driven particle models, with Boids model as the primary example; pheromone communication models, including the ant colony pheromone model which serves as the foundation for ant colony optimization; leadership decision models, utilizing the hierarchical dynamics model of pigeon flock as a prime instance; empirical research models, which employ the topological rule model of starling flock as a classic model. On this basis, each type of model is elaborated upon in terms of its typical model overview, applications, and model evaluation. More specifically, multi-agent swarm control, path optimization and obstacle avoidance, formation and consensus control, trajectory tracking in the dense crowd and social networks analysis are surveyed in the application of each category, respectively. Furthermore, the more precise and effective modeling techniques for leadership decision and empirical research models are described. Limitations and potential directions for further exploration in the study of SI are presented.
AB - Swarm Intelligence (SI) is a collective behavior that emerges from interaction between individuals in a group. Typical SI includes fish schooling, ant foraging, bird migration, and so on. A great deal of models have been introduced to characterize the mechanism of SI. This article reviews several typical models and classifies them into four categories: self-driven particle models, with Boids model as the primary example; pheromone communication models, including the ant colony pheromone model which serves as the foundation for ant colony optimization; leadership decision models, utilizing the hierarchical dynamics model of pigeon flock as a prime instance; empirical research models, which employ the topological rule model of starling flock as a classic model. On this basis, each type of model is elaborated upon in terms of its typical model overview, applications, and model evaluation. More specifically, multi-agent swarm control, path optimization and obstacle avoidance, formation and consensus control, trajectory tracking in the dense crowd and social networks analysis are surveyed in the application of each category, respectively. Furthermore, the more precise and effective modeling techniques for leadership decision and empirical research models are described. Limitations and potential directions for further exploration in the study of SI are presented.
KW - Ant colony optimization
KW - Empirical research models
KW - Leadership decision models
KW - Pheromone communication models
KW - Self-driven particle models
KW - Swarm intelligence
UR - https://www.scopus.com/pages/publications/85216341665
U2 - 10.1016/j.cja.2024.03.019
DO - 10.1016/j.cja.2024.03.019
M3 - 文献综述
AN - SCOPUS:85216341665
SN - 1000-9361
VL - 38
JO - Chinese Journal of Aeronautics
JF - Chinese Journal of Aeronautics
IS - 3
M1 - 102982
ER -