ECA — Endogenously-Constrained AI

Read full text
Authors: Wilson John Sterking Lauret
Cited by: 0

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