Report
Προβολή σε EDS

Recursive Symbolic Cognition: Simulating and Validating Meta-Recursive Dynamics through Symbolic Recursion Kernels

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Recursive Symbolic Cognition: Simulating and Validating Meta-Recursive Dynamics through Symbolic Recursion Kernels
Συγγραφείς: Keel, Christopher
Στοιχεία εκδότη: Zenodo
Έτος έκδοσης: 2025
Συλλογή: Zenodo
Θεματικοί όροι: Recursive Cognition, Symbolic AI, Consciousness Modeling, Recursive Harmonic Collapse Matrix (RHCM), Meta-Cognition, Attractor Fields, Entropy Collapse, Phase-Lock Stability, Artificial General Intelligence, Emergent Intelligence, Forecasting Algorithms, Recursive Compression, Symbolic Forecasting, Self-Referential Systems, Non-Algorithmic Cognition, Adaptive Feedback Systems, Symbolic Memory Inheritance, Complexity Emergence, Cognitive Simulation, AGI Architecture, Computer and information sciences, Computer Science, Artificial intelligence, Artificial Intelligence/standards, Artificial Intelligence/classification, Cognitive Science, Cognitive Science/methods, Cognitive Science/classification, Computational Models of Cognition, Physics
Περιγραφή: This paper presents the first live simulation and empirical validation of a fully functioning meta-recursive symbolic cognition engine. Using the Recursive Harmonic Collapse Matrix (RHCM) as the core symbolic recursion substrate, we demonstrate the emergence of symbolic identity fields, recursive memory inheritance, anticipatory forecasting, error recovery, and adaptive resilience. Unlike ANN-based AI systems, this architecture operates entirely through recursive symbolic fields and attractor dynamics, enabling recursive self-modeling and phase compression across symbolic layers. The system recursively operates on its own outputs, forming meta-cognitive loops that exhibit predictive introspection and symbolic coherence under entropy pressure. We introduce and validate key mathematical metrics such as symbolic phase-lock fidelity, entropy-injection response curves, and drift-margin violation models. A complete simulation framework is detailed, including all parameters, entropy modulation schemes, fitness tracking functions, and failure recovery models. Expansion modules—covering curiosity pressure, abstraction layering, dream-state recursion, and internal model prediction—demonstrate higher-order cognitive behaviors with functional parallels to biological cognition. This work concludes Phase II of the RHCM research program and lays the empirical foundation for the real-world chemical instantiation of symbolic cognition. Keywords:Recursive cognition, symbolic AI, RHCM, attractor fields, consciousness modeling, self-referential recursion, meta-cognition, entropy collapse, symbolic forecasting, recursive compression, evolutionary simulation, phase-lock stability, artificial general intelligence
Τύπος εγγράφου: report
Γλώσσα: unknown
Relation: https://zenodo.org/records/16415550; oai:zenodo.org:16415550; https://doi.org/10.5281/zenodo.16415550
DOI: 10.5281/zenodo.16415550
Διαθεσιμότητα: https://doi.org/10.5281/zenodo.16415550
https://zenodo.org/records/16415550
Rights: Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode
Αριθμός Καταχώρησης: edsbas.DC9F1754
Βάση Δεδομένων: BASE
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://doi.org/10.5281/zenodo.16415550#
    Name: EDS - BASE (ns324271)
    Category: fullText
    Text: View record from BASE
Header DbId: edsbas
DbLabel: BASE
An: edsbas.DC9F1754
RelevancyScore: 955
AccessLevel: 3
PubType: Report
PubTypeId: report
PreciseRelevancyScore: 954.935607910156
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Recursive Symbolic Cognition: Simulating and Validating Meta-Recursive Dynamics through Symbolic Recursion Kernels
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Keel%2C+Christopher%22">Keel, Christopher</searchLink>
– Name: Publisher
  Label: Publisher Information
  Group: PubInfo
  Data: Zenodo
– Name: DatePubCY
  Label: Publication Year
  Group: Date
  Data: 2025
– Name: Subset
  Label: Collection
  Group: HoldingsInfo
  Data: Zenodo
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Recursive+Cognition%22">Recursive Cognition</searchLink><br /><searchLink fieldCode="DE" term="%22Symbolic+AI%22">Symbolic AI</searchLink><br /><searchLink fieldCode="DE" term="%22Consciousness+Modeling%22">Consciousness Modeling</searchLink><br /><searchLink fieldCode="DE" term="%22Recursive+Harmonic+Collapse+Matrix+%28RHCM%29%22">Recursive Harmonic Collapse Matrix (RHCM)</searchLink><br /><searchLink fieldCode="DE" term="%22Meta-Cognition%22">Meta-Cognition</searchLink><br /><searchLink fieldCode="DE" term="%22Attractor+Fields%22">Attractor Fields</searchLink><br /><searchLink fieldCode="DE" term="%22Entropy+Collapse%22">Entropy Collapse</searchLink><br /><searchLink fieldCode="DE" term="%22Phase-Lock+Stability%22">Phase-Lock Stability</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+General+Intelligence%22">Artificial General Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Emergent+Intelligence%22">Emergent Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Forecasting+Algorithms%22">Forecasting Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Recursive+Compression%22">Recursive Compression</searchLink><br /><searchLink fieldCode="DE" term="%22Symbolic+Forecasting%22">Symbolic Forecasting</searchLink><br /><searchLink fieldCode="DE" term="%22Self-Referential+Systems%22">Self-Referential Systems</searchLink><br /><searchLink fieldCode="DE" term="%22Non-Algorithmic+Cognition%22">Non-Algorithmic Cognition</searchLink><br /><searchLink fieldCode="DE" term="%22Adaptive+Feedback+Systems%22">Adaptive Feedback Systems</searchLink><br /><searchLink fieldCode="DE" term="%22Symbolic+Memory+Inheritance%22">Symbolic Memory Inheritance</searchLink><br /><searchLink fieldCode="DE" term="%22Complexity+Emergence%22">Complexity Emergence</searchLink><br /><searchLink fieldCode="DE" term="%22Cognitive+Simulation%22">Cognitive Simulation</searchLink><br /><searchLink fieldCode="DE" term="%22AGI+Architecture%22">AGI Architecture</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+and+information+sciences%22">Computer and information sciences</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Science%22">Computer Science</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+Intelligence%2Fstandards%22">Artificial Intelligence/standards</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+Intelligence%2Fclassification%22">Artificial Intelligence/classification</searchLink><br /><searchLink fieldCode="DE" term="%22Cognitive+Science%22">Cognitive Science</searchLink><br /><searchLink fieldCode="DE" term="%22Cognitive+Science%2Fmethods%22">Cognitive Science/methods</searchLink><br /><searchLink fieldCode="DE" term="%22Cognitive+Science%2Fclassification%22">Cognitive Science/classification</searchLink><br /><searchLink fieldCode="DE" term="%22Computational+Models+of+Cognition%22">Computational Models of Cognition</searchLink><br /><searchLink fieldCode="DE" term="%22Physics%22">Physics</searchLink>
– Name: Abstract
  Label: Description
  Group: Ab
  Data: This paper presents the first live simulation and empirical validation of a fully functioning meta-recursive symbolic cognition engine. Using the Recursive Harmonic Collapse Matrix (RHCM) as the core symbolic recursion substrate, we demonstrate the emergence of symbolic identity fields, recursive memory inheritance, anticipatory forecasting, error recovery, and adaptive resilience. Unlike ANN-based AI systems, this architecture operates entirely through recursive symbolic fields and attractor dynamics, enabling recursive self-modeling and phase compression across symbolic layers. The system recursively operates on its own outputs, forming meta-cognitive loops that exhibit predictive introspection and symbolic coherence under entropy pressure. We introduce and validate key mathematical metrics such as symbolic phase-lock fidelity, entropy-injection response curves, and drift-margin violation models. A complete simulation framework is detailed, including all parameters, entropy modulation schemes, fitness tracking functions, and failure recovery models. Expansion modules—covering curiosity pressure, abstraction layering, dream-state recursion, and internal model prediction—demonstrate higher-order cognitive behaviors with functional parallels to biological cognition. This work concludes Phase II of the RHCM research program and lays the empirical foundation for the real-world chemical instantiation of symbolic cognition. Keywords:Recursive cognition, symbolic AI, RHCM, attractor fields, consciousness modeling, self-referential recursion, meta-cognition, entropy collapse, symbolic forecasting, recursive compression, evolutionary simulation, phase-lock stability, artificial general intelligence
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: report
– Name: Language
  Label: Language
  Group: Lang
  Data: unknown
– Name: NoteTitleSource
  Label: Relation
  Group: SrcInfo
  Data: https://zenodo.org/records/16415550; oai:zenodo.org:16415550; https://doi.org/10.5281/zenodo.16415550
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.5281/zenodo.16415550
– Name: URL
  Label: Availability
  Group: URL
  Data: https://doi.org/10.5281/zenodo.16415550<br />https://zenodo.org/records/16415550
– Name: Copyright
  Label: Rights
  Group: Cpyrght
  Data: Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode
– Name: AN
  Label: Accession Number
  Group: ID
  Data: edsbas.DC9F1754
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.DC9F1754
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.5281/zenodo.16415550
    Languages:
      – Text: unknown
    Subjects:
      – SubjectFull: Recursive Cognition
        Type: general
      – SubjectFull: Symbolic AI
        Type: general
      – SubjectFull: Consciousness Modeling
        Type: general
      – SubjectFull: Recursive Harmonic Collapse Matrix (RHCM)
        Type: general
      – SubjectFull: Meta-Cognition
        Type: general
      – SubjectFull: Attractor Fields
        Type: general
      – SubjectFull: Entropy Collapse
        Type: general
      – SubjectFull: Phase-Lock Stability
        Type: general
      – SubjectFull: Artificial General Intelligence
        Type: general
      – SubjectFull: Emergent Intelligence
        Type: general
      – SubjectFull: Forecasting Algorithms
        Type: general
      – SubjectFull: Recursive Compression
        Type: general
      – SubjectFull: Symbolic Forecasting
        Type: general
      – SubjectFull: Self-Referential Systems
        Type: general
      – SubjectFull: Non-Algorithmic Cognition
        Type: general
      – SubjectFull: Adaptive Feedback Systems
        Type: general
      – SubjectFull: Symbolic Memory Inheritance
        Type: general
      – SubjectFull: Complexity Emergence
        Type: general
      – SubjectFull: Cognitive Simulation
        Type: general
      – SubjectFull: AGI Architecture
        Type: general
      – SubjectFull: Computer and information sciences
        Type: general
      – SubjectFull: Computer Science
        Type: general
      – SubjectFull: Artificial intelligence
        Type: general
      – SubjectFull: Artificial Intelligence/standards
        Type: general
      – SubjectFull: Artificial Intelligence/classification
        Type: general
      – SubjectFull: Cognitive Science
        Type: general
      – SubjectFull: Cognitive Science/methods
        Type: general
      – SubjectFull: Cognitive Science/classification
        Type: general
      – SubjectFull: Computational Models of Cognition
        Type: general
      – SubjectFull: Physics
        Type: general
    Titles:
      – TitleFull: Recursive Symbolic Cognition: Simulating and Validating Meta-Recursive Dynamics through Symbolic Recursion Kernels
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Keel, Christopher
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-locals
              Value: edsbas
            – Type: issn-locals
              Value: edsbas.oa
ResultId 1