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Algorithmic Information Dynamics: A Computational Approach to Causality with Applications to Living Systems

Zenil, Hector; Kiani, Narsis A.; Tegn�r, Jesper

Publicado por Cambridge University Press, 2023

ISBN 10: 1108497667 ISBN 13: 9781108497664

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Condici�n: New. N� de ref. del art�culo: 26395973429

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Algorithmic Information Dynamics : A Computational Approach to Causality With Applications to Living Systems

Zenil, Hector; Kiani, Narsis A.; Tegn�r, Jesper

Publicado por Cambridge University Press, 2023

ISBN 10: 1108497667 ISBN 13: 9781108497664

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Algorithmic Information Dynamics: A Computational Approach to Causality with Applications to Living Systems

Zenil, Hector; Kiani, Narsis A.; Tegn�r, Jesper

Publicado por Cambridge University Press, 2023

ISBN 10: 1108497667 ISBN 13: 9781108497664

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Algorithmic Information Dynamics: A Computational Approach to Causality with Applications to Living Systems

Zenil, Hector; Kiani, Narsis A.; Tegn�r, Jesper

Publicado por Cambridge University Press, 2023

ISBN 10: 1108497667 ISBN 13: 9781108497664

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Algorithmic Information Dynamics (Hardcover)

Hector Zenil

Publicado por Cambridge University Press, Cambridge, 2023

ISBN 10: 1108497667 ISBN 13: 9781108497664

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Librería: Grand Eagle Retail, Fairfield, OH, Estados Unidos de America

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Hardcover. Condici�n: new. Hardcover. 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. Aimed at graduate students and researchers, this book offers a model-driven approach to the study and manipulation of dynamical systems. Based on an online course hosted by the Complexity Explorer, it uses analytical tools from information theory and complexity science to tackle key challenges in network and systems biology. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N� de ref. del art�culo: 9781108497664

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