From Collective Intelligence to Global Optimisation: An Agent-based Model Approach  

From Collective Intelligence to Global Optimisation: An Agent-based Model Approach | 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 From Collective Intelligence to Global Optimisation: An Agent-based Model Approach Martha Garzón, Lindsay Álvarez-Pomar, Sergio A. Rojas-Galeano This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5118788/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Feb, 2025 Read the published version in Computing → Version 1 posted You are reading this latest preprint version Abstract Drawing inspiration from online question-and-answer (Q&A) communities often regarded as embodiments of Collective Intelligence (CI), this study investigates the dynamics of reputation-driven and distributed network interactions in multi- agent systems as a model for problem-solving in global optimisation. We explore the interplay among diverse participants, including Solvers motivated by reputation and Users seeking net benefits, recognising its critical role in fostering success within these communities. Our study translates the principles of CI inherent in these interactions into a novel agent-based search algorithm for unconstrained optimisation of continuous-valued cost functions. Empirical testing across a suite of established benchmark problems allows a comparative analysis of its perfor- mance against alternative agent-based methodologies. These findings underscore the algorithm’s advantages across diverse optimisation 2D landscapes, highlighting the potential of the CI framework as a promising avenue in metaheuristic research. They illustrate how the interaction between individual actors and the collective, favours the emergence of global solutions in unknown environments, mirroring similar emergent phenomena observed in social organisations. Global optimisation metaheuristics collective intelligence genome Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 27 Feb, 2025 Read the published version in Computing → 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-5118788","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":379108448,"identity":"eaa8669f-fcdd-4cd8-acb5-d2e265a22283","order_by":0,"name":"Martha Garzón","email":"","orcid":"","institution":"Universidad Distrital Francisco José de Caldas","correspondingAuthor":false,"prefix":"","firstName":"Martha","middleName":"","lastName":"Garzón","suffix":""},{"id":379108449,"identity":"5d53704d-fa21-483a-8a11-eb6676a23008","order_by":1,"name":"Lindsay Álvarez-Pomar","email":"","orcid":"","institution":"Universidad Distrital Francisco José de Caldas","correspondingAuthor":false,"prefix":"","firstName":"Lindsay","middleName":"","lastName":"Álvarez-Pomar","suffix":""},{"id":379108450,"identity":"6564017c-840e-408a-9a7d-44dbe913983e","order_by":2,"name":"Sergio A. 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