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ISBN 10: 1108497667 ISBN 13: 9781108497664
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Publicado por Cambridge University Press, 2023
ISBN 10: 1108497667 ISBN 13: 9781108497664
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Idioma: Inglés
Publicado por Cambridge University Press, 2023
ISBN 10: 1108497667 ISBN 13: 9781108497664
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Idioma: Inglés
Publicado por Cambridge University Press, 2023
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Publicado por Cambridge University Press 2023-05-25, 2023
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Publicado por Cambridge University Press, 2023
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Idioma: Inglés
Publicado por Cambridge University Press, 2023
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Publicado por Cambridge University Press, 2023
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Añadir al carritoCondición: New. 2023. Hardcover. . . . . .
Idioma: Inglés
Publicado por Cambridge University Press, 2023
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Idioma: Inglés
Publicado por Cambridge University Press, 2023
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Idioma: Inglés
Publicado por Cambridge University Press, GB, 2023
ISBN 10: 1108497667 ISBN 13: 9781108497664
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Añadir al carritoHardback. Condición: New. 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.
Idioma: Inglés
Publicado por Cambridge University Press, 2023
ISBN 10: 1108497667 ISBN 13: 9781108497664
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Añadir al carritoCondición: New. 2023. Hardcover. . . . . . Books ship from the US and Ireland.
Idioma: Inglés
Publicado por Cambridge University Press, 2023
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Añadir al carritoCondición: New. Über den AutorHector 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 Dynam.
Idioma: Inglés
Publicado por Cambridge University Press Mai 2023, 2023
ISBN 10: 1108497667 ISBN 13: 9781108497664
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Añadir al carritoBuch. Condición: Neu. Neuware - 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.
Idioma: Inglés
Publicado por Cambridge University Press, 2023
ISBN 10: 1108497667 ISBN 13: 9781108497664
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Añadir al carritoBuch. Condición: Neu. Algorithmic Information Dynamics | A Computational Approach to Causality with Applications to Living Systems | Hector Zenil (u. a.) | Buch | Gebunden | Englisch | 2023 | Cambridge University Press | EAN 9781108497664 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
Idioma: Inglés
Publicado por Cambridge University Press, GB, 2023
ISBN 10: 1108497667 ISBN 13: 9781108497664
Librería: Rarewaves.com UK, London, Reino Unido
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Añadir al carritoHardback. Condición: New. 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.
Idioma: Inglés
Publicado por Cambridge University Press, Cambridge, 2023
ISBN 10: 1108497667 ISBN 13: 9781108497664
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
EUR 80,37
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Añadir al carritoHardcover. Condición: 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.
Idioma: Inglés
Publicado por Cambridge University Press, 2023
ISBN 10: 1108497667 ISBN 13: 9781108497664
Librería: Revaluation Books, Exeter, Reino Unido
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Añadir al carritoHardcover. Condición: Brand New. 345 pages. 9.61x6.69x0.81 inches. In Stock. This item is printed on demand.
Idioma: Inglés
Publicado por Cambridge University Press, 2023
ISBN 10: 1108497667 ISBN 13: 9781108497664
Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
EUR 82,50
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Añadir al carritoHardback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
Idioma: Inglés
Publicado por Cambridge University Press, Cambridge, 2023
ISBN 10: 1108497667 ISBN 13: 9781108497664
Librería: CitiRetail, Stevenage, Reino Unido
EUR 98,88
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Añadir al carritoHardcover. Condición: 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 our UK warehouse or from our Australian or US warehouses, depending on stock availability.