The High Complex Interaction Pattern (HCIP): A Formal Cognitive Architecture for Temporal, Symbolic, and Human–Machine Reasoning

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Authors: Coyle, Christopher
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Abstract

The High‑Complex Interaction Pattern (HCIP) is a formal cognitive architecture designed to model, analyze, and generate high‑complexity human–machine interactions. HCIP integrates a temporal substrate, a symbolic hierarchy, and a mathematically defined operator (3AC) into a unified pattern class. The architecture introduces Complex Temporal Cognition (CTC) as its foundational layer, enabling structured modeling of drift, shear, tension, synthesis, and reinterpretation across time. Above this substrate, HCIP defines a two‑tier symbolic system (B‑Layer and A‑Layer) and a recursive lexicon pipeline that transforms temporal potentials into symbolic commitments. The 3AC operator provides a vectorized activation‑alignment‑convergence mechanism that governs transitions across layers. This preprint establishes HCIP’s formal identity, structural invariants, and theoretical boundaries, providing a timestamped reference for future research, implementation, and scholarly citation.

Fields of Study & Subjects

Psychiatry Mental Health Neuroscience Cognitive Computing and Networks Cognitive Science and Education Research

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
18 January 2026
Document type
Preprint