{"title":"Modeling Robot Swarms Using Integrals of Birth-Death Processes","authors":"Yara Khaluf, M. Dorigo","doi":"10.1145/2870637","DOIUrl":null,"url":null,"abstract":"This article investigates the use of the integral of linear birth-death processes in the context of analyzing swarm robotics systems. We show that when a robot swarm can be modeled as a linear birth-death process, well-established results can be used to compute the expected value and/or the distribution of important swarm performance measures, such as the swarm activity time or the swarm energy consumption. We also show how the linear birth-death model can be used to estimate the long-term value of such performance measures and design robot controllers that satisfy constraints on these measures.","PeriodicalId":377078,"journal":{"name":"ACM Transactions on Autonomous and Adaptive Systems (TAAS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Autonomous and Adaptive Systems (TAAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2870637","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
This article investigates the use of the integral of linear birth-death processes in the context of analyzing swarm robotics systems. We show that when a robot swarm can be modeled as a linear birth-death process, well-established results can be used to compute the expected value and/or the distribution of important swarm performance measures, such as the swarm activity time or the swarm energy consumption. We also show how the linear birth-death model can be used to estimate the long-term value of such performance measures and design robot controllers that satisfy constraints on these measures.