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 studying and manipulating dynamical systems . It draws tools from network and systems biology, 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 ebook valuable for graduate students and researchers in a wide number of fields in science from physics to cell biology to cognitive sciences.
978-1108497664, 978-1108659260
NOTE: This sale only includes the ebook Algorithmic Information Dynamics: A Computational Approach to Causality with Applications to Living Systems in PDF. No access codes are included.
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