Swarm Intelligence最新文献_第3页

Effect of Swarm Density on Collective Tracking Performance 群体密度对集体跟踪性能的影响

IF 2.6 4区计算机科学

Swarm Intelligence Pub Date : 2023-01-25 DOI: 10.48550/arXiv.2301.10692

H. L. Kwa, J. Philippot, Roland Bouffanais

{"title":"Effect of Swarm Density on Collective Tracking Performance","authors":"H. L. Kwa, J. Philippot, Roland Bouffanais","doi":"10.48550/arXiv.2301.10692","DOIUrl":"https://doi.org/10.48550/arXiv.2301.10692","url":null,"abstract":"How does the size of a swarm affect its collective action? Despite being arguably a key parameter, no systematic and satisfactory guiding principles exist to select the number of units required for a given task and environment. Even when limited by practical considerations, system designers should endeavor to identify what a reasonable swarm size should be. Here, we show that this fundamental question is closely linked to that of selecting an appropriate swarm density. Our analysis of the influence of density on the collective performance of a target tracking task reveals different `phases' corresponding to markedly distinct group dynamics. We identify a `transition' phase, in which a complex emergent collective response arises. Interestingly, the collective dynamics within this transition phase exhibit a clear trade-off between exploratory actions and exploitative ones. We show that at any density, the exploration-exploitation balance can be adjusted to maximize the system's performance through various means, such as by changing the level of connectivity between agents. While the density is the primary factor to be considered, it should not be the sole one to be accounted for when sizing the system. Due to the inherent finite-size effects present in physical systems, we establish that the number of constituents primarily affects system-level properties such as exploitation in the transition phase. These results illustrate that instead of learning and optimizing a swarm's behavior for a specific set of task parameters, further work should instead concentrate on learning to be adaptive, thereby endowing the swarm with the highly desirable feature of being able to operate effectively over a wide range of circumstances.","PeriodicalId":51284,"journal":{"name":"Swarm Intelligence","volume":"1 1","pages":"253-281"},"PeriodicalIF":2.6,"publicationDate":"2023-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75009043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}