Interaction Rules Supporting Effective Flocking Behavior.

IF 1.6 4区 计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Artificial Life Pub Date : 2024-08-01 DOI:10.1162/artl_a_00438
Nicola Milano, Stefano Nolfi
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Abstract

Several simulation models have demonstrated how flocking behavior emerges from the interaction among individuals that react to the relative orientation of their neighbors based on simple rules. However, the precise nature of these rules and the relationship between the characteristics of the rules and the efficacy of the resulting collective behavior are unknown. In this article, we analyze the effect of the strength with which individuals react to the orientation of neighbors located in different sectors of their visual fields and the benefit that could be obtained by using control rules that are more elaborate than those normally used. Our results demonstrate that considering only neighbors located on the frontal side of the visual field permits an increase in the aggregation level of the swarm. Using more complex rules and/or additional sensory information does not lead to better performance.

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支持有效成群行为的互动规则
一些模拟模型已经证明了成群行为是如何从个体间的相互作用中产生的,这些个体根据简单的规则对其邻居的相对方位做出反应。然而,这些规则的确切性质以及规则的特征与由此产生的集体行为的有效性之间的关系尚不清楚。在本文中,我们分析了个体对位于其视野不同区域的邻居的方位做出反应的强度所产生的影响,以及使用比通常使用的控制规则更复杂的控制规则所能带来的益处。我们的研究结果表明,只考虑位于视野正面的邻居可以提高蜂群的聚集水平。使用更复杂的规则和/或额外的感官信息并不会带来更好的性能。
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来源期刊
Artificial Life
Artificial Life 工程技术-计算机:理论方法
CiteScore
4.70
自引率
7.70%
发文量
38
审稿时长
>12 weeks
期刊介绍: Artificial Life, launched in the fall of 1993, has become the unifying forum for the exchange of scientific information on the study of artificial systems that exhibit the behavioral characteristics of natural living systems, through the synthesis or simulation using computational (software), robotic (hardware), and/or physicochemical (wetware) means. Each issue features cutting-edge research on artificial life that advances the state-of-the-art of our knowledge about various aspects of living systems such as: Artificial chemistry and the origins of life Self-assembly, growth, and development Self-replication and self-repair Systems and synthetic biology Perception, cognition, and behavior Embodiment and enactivism Collective behaviors of swarms Evolutionary and ecological dynamics Open-endedness and creativity Social organization and cultural evolution Societal and technological implications Philosophy and aesthetics Applications to biology, medicine, business, education, or entertainment.
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