Format:
1 online resource (xi, 331 pages)
,
digital, PDF file(s).
ISBN:
9781108596619
,
9781108497664
Content:
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.
Note:
Title from publisher's bibliographic system (viewed on 11 May 2023)
Additional Edition:
ISBN 9781108497664
Additional Edition:
Erscheint auch als Druck-Ausgabe ISBN 9781108497664
Language:
English
DOI:
10.1017/9781108596619
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