Algorithmic Information Dynamics
A Computational Approach to Causality with Applications to Living Systems
Published on 17. May 2023
978-1-108-65926-0 (ISBN)
Description
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.
More details
Language
English
Place of publication
Cambridge
United Kingdom
Illustrations
Worked examples or Exercises
File size
19,77 MB
ISBN-13
978-1-108-65926-0 (9781108659260)
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Schweitzer Classification
Other editions
Additional editions
Hector Zenil | Narsis A. Kiani | Jesper Tegner
Algorithmic Information Dynamics
A Computational Approach to Causality with Applications to Living Systems
Book
05/2023
Cambridge University Press
€78.00
Shipment within 15-20 days
Persons
Content
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.
