Multi‐Agent Imitation Behavior Based on Information Interaction

As a common social phenomenon, group imitation behavior holds significant research value in the fields of biological group collaboration and artificial swarm intelligence. This paper constructs a behavior imitation model integrating information dissemination mechanisms based on the theory of multiagent systems. The model aims to reveal the influence mechanism of group dynamic characteristics and information interaction intensity on the consistency of group behavior. The model architecture consists of two parts. The first part is an information dissemination model improved upon the SIR model, which introduces a perception radius to analyze how neighboring interactions affect the information diffusion rate. The second part is a multiagent group aggregation model based on social mechanics, enabling individuals to form groups through parameters like attraction, repulsion, speed, and movement direction. Groups spread aggregation and imitation information through interactions with neighboring individuals. Then, based on the breadth of the information they receive, they imitate exemplary groups through intergroup imitation effects. Through complex system simulations, the experimental results show that the consistency of group imitation behavior is positively correlated with the perception radius of individuals. This research provides a new modeling framework and analytical perspective for understanding the emergence mechanism of swarm intelligence.

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Publication Details

Journal
Complexity
Published
2025-01-01
DOI
https://doi.org/10.1155/cplx/8828678
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Multi‐Agent Imitation Behavior Based on Information Interaction

Xuebo Chen, Meijuan Li, Peng Yu, Chen Guo
Complexity
Distributed Control Multi-Agent Systems
article

Multi‐Agent Imitation Behavior Based on Information Interaction

Xuebo Chen, Meijuan Li, Peng Yu, Chen Guo
article en

Abstract

As a common social phenomenon, group imitation behavior holds significant research value in the fields of biological group collaboration and artificial swarm intelligence. This paper constructs a behavior imitation model integrating information dissemination mechanisms based on the theory of multiagent systems. The model aims to reveal the influence mechanism of group dynamic characteristics and information interaction intensity on the consistency of group behavior. The model architecture consists of two parts. The first part is an information dissemination model improved upon the SIR model, which introduces a perception radius to analyze how neighboring interactions affect the information diffusion rate. The second part is a multiagent group aggregation model based on social mechanics, enabling individuals to form groups through parameters like attraction, repulsion, speed, and movement direction. Groups spread aggregation and imitation information through interactions with neighboring individuals. Then, based on the breadth of the information they receive, they imitate exemplary groups through intergroup imitation effects. Through complex system simulations, the experimental results show that the consistency of group imitation behavior is positively correlated with the perception radius of individuals. This research provides a new modeling framework and analytical perspective for understanding the emergence mechanism of swarm intelligence.

ComplexityVol. 2025(1)
University of Science and Technology Liaoning (CN), Wuxi Taihu Hospital (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 69%
Distributed Control Multi-Agent Systems
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