This work presents the complete foundational architecture of Crowd-Based Dynamics (CBD), a theoretical framework dedicated to the study of collective, cognitive, informational, financial, institutional, and artificial systems. CBD introduces a structural reading approach based on the interaction between psychodynamic depth (Aψ), contextual opportunities and disorders O(t)·D(t), and active temporality F(t). The framework formalizes the mechanisms through which systems accumulate information, propagate states, develop memory effects, undergo saturation, and progressively lose governability. The corpus establishes a coherent set of foundational laws, including Mimetic Saturation, Informational Tipping, Temporal Governability, Conditional Reversibility, and the Cognitive Cost of Governance. These laws are integrated into a unified architecture designed to identify structural regimes rather than predict isolated events. CBD is positioned within the broader field of complex adaptive systems and maintains formal correspondences with UCQ, DUAL, ECA, SMOT, and RAG-RES. The framework provides a general operator for understanding regime transitions, systemic stability, critical thresholds, and the limits of governability across diverse domains.
Wilson John Sterking LAURET (Tue,) studied this question.