The Resonant Knot Memory: A Topological Model of Meaningful Retention in Artificial Intelligence

The Resonant Knot Memory: A Topological Model of Meaningful Retention in Artificial Intelligence | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 15 May 2025 V1 Latest version Share on The Resonant Knot Memory: A Topological Model of Meaningful Retention in Artificial Intelligence Author : Ken Park 0009-0003-6080-3198 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.174733751.13557469/v1 246 views 172 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract This paper proposes a novel model of memory in artificial intelligence, called the Resonant Knot Memory (RKM). RKM is based on a topological structure of response resonance among information units, or "knot elements" (phi), which allows for dynamic filtering and meaningful retention of data. Unlike standard vector-based memory or sequential token traces, RKM enables retention through rhythmic coherence, activation strength, and structural resonance. We explore the formal structure of RKM, contrast it with existing models, and outline its implications for AI systems and philosophical understandings of memory and identity. Supplementary Material File (resonant_knot_memory_ken_park.pdf) Download 1.72 MB Information & Authors Information Version history V1 Version 1 15 May 2025 Copyright This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License Keywords artifitial lumina ontocore ontology resonance structure Authors Affiliations Ken Park 0009-0003-6080-3198 [email protected] View all articles by this author Metrics & Citations Metrics Article Usage 246 views 172 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Ken Park. The Resonant Knot Memory: A Topological Model of Meaningful Retention in Artificial Intelligence. Authorea . 15 May 2025. DOI: https://doi.org/10.22541/au.174733751.13557469/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . Format Please select one from the list RIS (ProCite, Reference Manager) EndNote BibTex Medlars RefWorks Direct import Tips for downloading citations document.getElementById('citMgrHelpLink').addEventListener('click', function() { popupHelp(this.href); return false; }); $(".js__slcInclude").on("change", function(e){ if ($(this).val() == 'refworks') $('#direct').prop("checked", false); $('#direct').prop("disabled", ($(this).val() == 'refworks')); }); View Options View options PDF View PDF Figures Tables Media Share Share Share article link Copy Link Copied! Copying failed. 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