Machine Learning Techniques for Adaptive Consensus Mechanism in Blockchain Systems

Machine Learning Techniques for Adaptive Consensus Mechanism in Blockchain Systems | 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 Machine Learning Techniques for Adaptive Consensus Mechanism in Blockchain Systems Christina-Eleanna Samara, Gregorios Georgios Kapadoukas, Christos Makris This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7892207/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 9 You are reading this latest preprint version Abstract Blockchain technology has emerged as a critical infrastructure for the development of decentralized applications and services, offering transparency, security, and resilience. Central to its operation is the consensus mechanism, which ensures that all participants in the system agree on its state. However, classic consensus algorithms often have disadvantages in terms of performance and security when conditions and network load change, as they are not able to adapt dynamically. This paper studies machine learning techniques for developing a more flexible and adaptive consensus mechanism. Specifically, two methods are used: reinforcement learning using Deep Q-Networks, and the LinTS algorithm, which belongs to the Multi-Armed Bandits category. The goal is to select the most appropriate consensus algorithm depending on the system conditions and to maximize metrics such as transaction rate, resource consumption, stability, and security. The experimental results show that the use of machine learning models leads to improved performance compared to static consensus algorithms, highlighting the importance of adaptability in real blockchain environments. The use of machine learning in real blockchain environments shows many positive results, indicating that research in this field should continue. Finally, future directions are proposed that can further enhance the adaptability and efficiency of consensus systems. Blockchain Consensus Mechanisms Machine Learning Reinforcement Learning Deep Q-Networks Multi-Armed Bandits Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 27 Mar, 2026 Reviews received at journal 04 Mar, 2026 Reviews received at journal 03 Mar, 2026 Reviewers agreed at journal 23 Feb, 2026 Reviewers agreed at journal 23 Feb, 2026 Reviewers invited by journal 23 Feb, 2026 Editor assigned by journal 10 Nov, 2025 Submission checks completed at journal 18 Oct, 2025 First submitted to journal 18 Oct, 2025 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. 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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-7892207","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":595939636,"identity":"535649bb-6e9b-429f-ad20-4d381fefcbb0","order_by":0,"name":"Christina-Eleanna Samara","email":"","orcid":"","institution":"University of Patras","correspondingAuthor":false,"prefix":"","firstName":"Christina-Eleanna","middleName":"","lastName":"Samara","suffix":""},{"id":595939639,"identity":"df4e1522-cdc9-4d46-a4c6-5fcafb10c4bc","order_by":1,"name":"Gregorios Georgios Kapadoukas","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCElEQVRIie3RMUvDQBTA8XcUkuWa+RUhfoULB9mkX+UOIZNboTgmFC7L4Vzpp5B+gKYE2qU4Kw1SCXQ+EEQkWK1F0OHajkLvP703/HjDA3C5/mUkLZtrLyR5ejRpZSu6CHhLF7udHib+gLVVKPOhOJKwZaYQvZi3b+tnQ1R13j0rawPvT3ZSTRUymoSdUcKRqHWkgyRGctOzkwepUOCMRyMRA1El0RS+Bi32k4Jt5ORx/rolXU39F3OADKJUeDIb0u8rUlPKEN7spFNNsxoKjxN91UNxv77UC9pHmdpJsMxXJfnYvnJ+Z0y/usi1PzamsRPA34uAYjdIZRd/CfwQaPYQl8vlOrU+AforWvubDoMCAAAAAElFTkSuQmCC","orcid":"","institution":"University of Patras","correspondingAuthor":true,"prefix":"","firstName":"Gregorios","middleName":"Georgios","lastName":"Kapadoukas","suffix":""},{"id":595939646,"identity":"ab87dc43-06e2-4ce9-ac67-bd98aaf9f04f","order_by":2,"name":"Christos Makris","email":"","orcid":"","institution":"University of Patras","correspondingAuthor":false,"prefix":"","firstName":"Christos","middleName":"","lastName":"Makris","suffix":""}],"badges":[],"createdAt":"2025-10-18 08:53:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7892207/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7892207/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104399895,"identity":"d7cb4e76-30ff-4fb8-989c-96c98337cd6e","added_by":"auto","created_at":"2026-03-11 12:08:05","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1339684,"visible":true,"origin":"","legend":"","description":"","filename":"MachineLearningTechniquesforAdaptiveConsensusMechanisminBlockchainSystems.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7892207/v1_covered_8c514093-596f-46bc-afe1-09ea4ed88f88.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Machine Learning Techniques for Adaptive Consensus Mechanism in Blockchain Systems","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"knowledge-and-information-systems","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"kais","sideBox":"Learn more about [Knowledge and Information Systems](http://link.springer.com/journal/10115)","snPcode":"10115","submissionUrl":"https://submission.nature.com/new-submission/10115/3","title":"Knowledge and Information Systems","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Blockchain, Consensus Mechanisms, Machine Learning, Reinforcement Learning, Deep Q-Networks, Multi-Armed Bandits","lastPublishedDoi":"10.21203/rs.3.rs-7892207/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7892207/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Blockchain technology has emerged as a critical infrastructure for the development of decentralized applications and services, offering transparency, security, and resilience. 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