Zenil H. Algorithmic Information Dynamics. A Computational Approach...2023 torrent

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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.
Preface
Introduction: Living Systems, Causality, and Information
Part I Preliminaries
A Computational Approach to Causality
Networks: From Structure to Dynamics
Information and Computability Theories
Part II Theory and Methods
Algorithmic Information Theory
The Coding Theorem Method (CTM)
The Block Decomposition Method (BDM)
Graph and Tensor Complexity
Algorithmic Information Dynamics (AID)
Part III Applications
From Theory to Practice
Algorithmic Dynamics in Artificial Environments
Applications to Integer and Behavioural Sequences
Applications to Evolutionary Biology