ECA — Endogenously-Constrained AI
Abstract
This document defines Endogenously-Constrained AI (ECA) as the implementation layer of the Crowd-Based Dynamics framework.It translates CBD structural limits into internal constraints governing artificial systems and socio-technical architectures.ECA embeds constraints endogenously, avoiding ex post external control mechanisms.The text grounds ECA in the CBD canonical formula, used as a design grammar rather than a predictive model.It addresses temporal governability, saturation management, mimetic load, and reversibility in artificial agents.Clear boundaries are set, excluding prediction, optimization, or normative enforcement.The document positions ECA as a constrained implementation ensuring structural alignment under scale and complexity.
Fields of Study & Subjects
Complex Systems and Dynamics
Ethics and Social Impacts of AI
Multi-Agent Systems and Negotiation
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 10 February 2026
- Language
- EN