Human-Centric AIX™ Stack: Presence Engine™ and the C³ Model
This technical specification documents the C³ Model (Context Capture, Coherence, and Continuity), a recursive cognitive architecture enabling stateful context awareness in AI systems across emotional, linguistic, and temporal domains. The C³ Model functions as the cognitive subsystem of the Presence Engine™, implementing persistent identity and behavioral continuity that standard RAG systems and memory-enhanced LLMs cannot provide. The architecture addresses architectural amnesia in current AI systems. While foundation models process information within sessions, they lack mechanisms to maintain dispositional continuity, emotional coherence, and contextual integrity across interactions. The C³ Model solves this through a five-layer recursive loop (Perceptual Input › State Construction › Integrative Awareness › Behavioral Adaptation › Meta-Learning) with dynamic decay functions, conflict resolution, and uncertainty quantification. Key technical contributions include: (1) hybrid dispositional modeling using OCEAN/HEXACO personality frameworks, (2) domain-specific context persistence with empirically calibrated decay rates, (3) real-time conflict resolution between emotional, linguistic, and temporal signals, and (4) privacy-first local processing with encrypted vector storage. Implementation validated using Anthropic Claude 3 Haiku with 100-user pilot study planned for Q4 2025. This document establishes prior art for continuity architecture as AI infrastructure. Keywords: continuity architecture, stateful AI, context awareness, emotional intelligence, C³ Model, Presence Engine, OCEAN personality modeling, HEXACO framework, persistent identity, behavioral coherence, recursive cognition, affective computing, privacy-first AI, conversational continuity, dispositional modeling
Institutions
- ANT Foundation Italy Onlus (IT)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-10-20
- DOI
- https://doi.org/10.5281/zenodo.17497393
- Primary Topic
- Emotion and Mood Recognition
- Type
- article
- Field-Weighted Citation Impact
- 0.00