Exploring Behavioral Diversity in Robot Swarms: A Comparative Study of Evolutionary Strategies for Aggregation Tasks

Exploring Behavioral Diversity in Robot Swarms: A Comparative Study of Evolutionary Strategies for Aggregation Tasks | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Exploring Behavioral Diversity in Robot Swarms: A Comparative Study of Evolutionary Strategies for Aggregation Tasks Paolo Pagliuca, Alessandra Vitanza This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4684526/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 23 Mar, 2025 Read the published version in IEEE Access → Version 1 posted You are reading this latest preprint version Abstract Collective decision-making is widely observed in natural organisms, especially insects and animals. In this regard, aggregation represents one of the paramount behaviors, as it can be useful for protecting groups against predators or speeding up the foraging process. In the field of autonomous robotics, aggregation is modeled through a series of alternative paradigms, among which evolutionary algorithms are considered a convenient tool. In this work, we compared three modern evolutionary strategies --- CMA-ES, xNES and OpenAI-ES --- for their ability to evolve an aggregation behavior in a swarm of robots. Specifically, we systematically varied the number of agents in the group, the environmental conditions (i.e., the number of target nests) and the parameters tuning the fitness function. Our aim is to verify whether and how the selected methods are effective at addressing the problem. The results we obtained indicate how the OpenAI-ES achieves better performance in all the considered scenarios. Furthermore, it displays qualitatively more interesting strategies than the other two methods. Aggregation collective decision-making behavioral diversity evolutionary strategies Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 23 Mar, 2025 Read the published version in IEEE Access → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4684526","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":332824254,"identity":"db9f26a5-b51c-4d74-ad02-25cb21dced65","order_by":0,"name":"Paolo Pagliuca","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCklEQVRIiWNgGAWjYHACxgNgip2xAUja8MDF2fDogWhhBmtJ44ErZcOjB6oFTB5GMh2HFnP2wwcOfGC4Iy/vzNwm8aPmvIz8/OYHDD933GPgk2/AqsWyJy3h4AyGZ4YbDzO2SfYcu81jcIzNgLH3TDFOhxkcyDE4zMNwmHFjM2ObNAMbUAsbD9BfbQm4tZx/A9ZiD9Hy7xyPfBshLTcgtiTOByqTZmw7wMNwjIAWyxnPgH4xeJa8gZmx2bK3LxnolzSDg71tCTxsbAnYQ4w/+eCDDxV3bOe3tz+88eObnb188+GHD362JcjJNx/A7jBoIIAQAoDYPFhUI2kBqsERCaNgFIyCUTAKGBgAIUVXYlJpvrQAAAAASUVORK5CYII=","orcid":"","institution":"National Research Council (CNR)","correspondingAuthor":true,"prefix":"","firstName":"Paolo","middleName":"","lastName":"Pagliuca","suffix":""},{"id":332824255,"identity":"385bb208-8a19-4594-b4d3-d15379ae778b","order_by":1,"name":"Alessandra Vitanza","email":"","orcid":"","institution":"National Research Council (CNR)","correspondingAuthor":false,"prefix":"","firstName":"Alessandra","middleName":"","lastName":"Vitanza","suffix":""}],"badges":[],"createdAt":"2024-07-04 07:22:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4684526/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4684526/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1109/ACCESS.2025.3554344","type":"published","date":"2025-03-24T00:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":82394111,"identity":"7381decd-c23a-4bfb-94eb-9672c998f9e6","added_by":"auto","created_at":"2025-05-09 19:36:09","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6654563,"visible":true,"origin":"","legend":"","description":"","filename":"paperSwarmIntelligencefinal1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4684526/v1_covered_32f0ee35-536e-4d33-a697-07e1067a1939.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Exploring Behavioral Diversity in Robot Swarms: A Comparative Study of Evolutionary Strategies for Aggregation Tasks","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Aggregation, collective decision-making, behavioral diversity, evolutionary strategies","lastPublishedDoi":"10.21203/rs.3.rs-4684526/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4684526/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Collective decision-making is widely observed in natural organisms, especially insects and animals. 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