Description
Biological systems are intricate networks forged through complex interactions, and understanding these networks poses a significant challenge, particularly when reconstructing causal knowledge from noisy and often incomplete data sets. This is a core focus in the evolving domain of systems biology. Drawing upon the foundational lessons of an online course offered by the renowned Santa Fe Institute’s Complexity Explorer, this book delves into the innovative field of **Algorithmic Information Dynamics**. This model-driven methodology enables a comprehensive investigation of both natural and artificial dynamical systems, harnessing principles from network biology, information theory, complexity science, and dynamical systems.
The book provides a robust theoretical and methodological framework designed to facilitate exploration into these complex systems, allowing researchers to generate computable models that elucidate phenomena within adaptable systems. This unique approach makes the ebook an invaluable resource for graduate students and researchers across diverse scientific disciplines, including physics, cell biology, and cognitive sciences.
Expect to uncover a treasure trove of insights on the mechanisms that govern dynamical systems through the lens of information dynamics. Whether you’re seeking to comprehend the complexity of living systems or explore computational applications, this work serves as a critical guide in bridging theory and practice.
**ISBNs: 978-1108659260, 978-1108497664**
**NOTE: This sale includes only the ebook version of *Algorithmic Information Dynamics: A Computational Approach to Causality with Applications to Living Systems* in PDF format. Please note that no access codes are included.**
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