Hector Zenil, Narsis A. Kiani, Jesper Tegner

Algorithmic Information Dynamics (eBook, PDF)

• Format: PDF

Produktbeschreibung

Biological systems are extensively studied as interactions forming complex networks. Reconstructing causal knowledge from, and principles of, these networks from noisy and incomplete data is a challenge in the field of systems biology. Based on an online course hosted by the Santa Fe Institute Complexity Explorer, this book introduces the field of Algorithmic Information Dynamics, a model-driven approach to the study and manipulation of dynamical systems . It draws tools from network and systems biology as well as information theory, complexity science and dynamical systems to study natural and artificial phenomena in software space. It consists of a theoretical and methodological framework to guide an exploration and generate computable candidate models able to explain complex phenomena in particular adaptable adaptive systems, making the book valuable for graduate students and researchers in a wide number of fields in science from physics to cell biology to cognitive sciences.

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Produktdetails

• Verlag: Cambridge University Press
• Erscheinungstermin: 25. Mai 2023
• Englisch
• ISBN-13: 9781108659260
• Artikelnr.: 68962937

Autorenporträt

Hector Zenil is a senior researcher at the Alan Turing Institute, British Library, researcher at the Department of Chemical Engineering and Biotechnology, University of Cambridge and the leader of the Algorithmic Dynamics Lab at the Karolinska Institute in Sweden. Previous positions include Computer Science faculty member at the University of Oxford, NASA Payload team member for the Mars Gravity Biosatellite at the Massachusetts Institute of Technology, and researcher at the Evolutionary and Behavioural Theory Lab at the University of Sheffield. He helped develop the factual answering Artificial Intelligence engine behind Siri and Alexa at Wolfram Research. He has published over 120 peer-reviewed papers, edited six books, is Editor of the journal Complex Systems, and the author of Methods and Applications of Algorithmic Complexity (2022).

Inhaltsangabe

Introduction
Part I. Preliminaries: 1. A computational approach to causality
2. Networks: from structure to dynamics
3. Information and computability theories
Part II. Theory and Methods: 4. Algorithmic information theory
5. The coding theorem method (CTM)
6. The block decomposition method (BDM)
7. Graph and tensor complexity
8. Algorithmic information dynamics (AID)
Part III. Applications: 9. From theory to practice
10. Algorithmic dynamics in artificial environments
11. Applications to integer and behavioural sequences
12. Applications to evolutionary biology
Postface
Appendix: Mutual and conditional BDM
Glossary.