The Entropic Markov Model (EMM): System and Method for Predicting Dynamic Outcomes in Human, Organizational, and Socio-Technical Systems

The Entropic Markov Model (EMM) provides a unified computational framework for analyzing and predicting transitions in complex adaptive systems.

By introducing entropy-weighted probabilistic transitions and behavioral-energy coefficients, EMM captures both structural uncertainty and motivational momentum within dynamic environments.

The model applies to human, organizational, and socio-technical systems where state changes are influenced by internal energy and disorder.

This paper presents the theoretical basis, algorithmic structure, and multi-domain applicability of EMM, including organizational transformation, behavioral analytics, and macro-system forecasting.

Patent Pending – U.S. Application No. 19/362,400.