Complexity Measurements and Causation for Dynamic Complex Systems

Author:   Juan Guillermo Diaz Ochoa
Publisher:   Springer International Publishing AG
ISBN:  

9783031847080


Pages:   159
Publication Date:   14 March 2025
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Complexity Measurements and Causation for Dynamic Complex Systems


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Author:   Juan Guillermo Diaz Ochoa
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
ISBN:  

9783031847080


ISBN 10:   3031847083
Pages:   159
Publication Date:   14 March 2025
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Concepts of Causality and Systems theory.- A brief overview on Dynamic Complex Systems And Causal Inference.- Elastic States and Complex Dynamics in Mechanistic Models.- A cartography of complexity.- The implications of relative causal inference for the understanding of complex systems.

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Author Information

Juan G. Diaz Ochoa is a physicist and entrepreneur with an interest in the fundamental aspects of complex systems, philosophy and innovation. Aside from studying astrophysics at the National Observatory of Colombia (rotating neutron stars in non-Newtonian approximations), Juan G. Diaz Ochoa obtained his PhD at the University of Mainz in theoretical physics and condensed matter, specifically molecular dynamics of polymer melts, where he completed his doctorate in physics within Professor Binder's group. After different stations, including the Max Planck Institute for complex technical systems, he moved to industry, worked with different companies and founded his own enterprises in the field of biomedicine. He is also a lecturer in mathematics and algorithms and complexity at DHBW in Stuttgart and a member of various societies, including the German Physical Society and DECHEMA. In recent years, he has explored fundamental questions regarding systems theory and biology and has made efforts to develop mathematical methods applied to various complex systems, from condensed matter to biomedicine. He has been involved in the development of novel mathematical concepts and artificial intelligence algorithms applied to medicine, with a focus on transparent artificial intelligence architectures, graph knowledge, topological machine learning and language models. He is also actively working on ethical issues in machine learning and artificial intelligence and coedited an article collection on transparent machine learning in medicine.

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