Dialogic Intelligence Architecture: Technical Formalization - English Version

Technical formalization and reference implementation of Dialogic Intelligence Architecture (DIA) - a production-ready framework for stateful AI agents. This document provides complete architectural specification DIA = (I, S, M, P, C) with formal definitions, code examples, and performance benchmarks. Includes: - Hierarchical Identity Core (I) with RBAC and audit trails - Structured State (Sₜ) management with serialization protocols - Memory Engine (M) algorithms for autonomous updates - Processor (P) integration specifications for major LLMs - Transparency Config (C) for enterprise-grade observability Validated Results: - 90-95% memory recall accuracy vs 10-20% in conventional systems - 67-92% token efficiency gains (1.2K vs 8-15K tokens per request) - 98% identity consistency with full session serialization - Battle-tested in healthcare, finance, and industrial applications Provides implementation guides for three complexity levels: 1. Tabular memory systems (Cinema Guide - 94% accuracy) 2. Graph-based knowledge agents (Indigo - 98% stability) 3. Metacognitive architectures (Superposition Module) Repository: https://github.com/Singular-MOL/dialogic-intelligence-architecture Contact: The MOL Foundation: [email protected] COMPLETE DIA FRAMEWORK This work is part of the comprehensive research on Dialogic Intelligence Architecture. The complete system includes: • Technical Formalization (this document) • Methodological Basis (https://doi.org/10.5281/zenodo.17699476) • Core Whitepaper (https://doi.org/10.5281/zenodo.17699367) THEORETICAL FOUNDATION Based on the Law of Minimal Ontological Load (DOI: 10.5281/zenodo.17445023)