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Algorithmic Information Dynamics
A book at the intersection of the most exciting current scientific trends in complexity science, information theory and living systems.
Networks of Networks in Biology
Biological systems are extremely complex and have emergent properties that cannot be explained or even predicted by studying their individual parts in isolation. The reductionist approach, although successful in the early days of molecular biology, underestimates this complexity. As the amount of available data grows, so it will become increasingly important to be able to analyse and integrate these large data sets. This book introduces novel approaches and solutions to the Big Data problem in biomedicine, and presents new techniques in the field of graph theory for handling and processing multi-type large data sets. By discussing cutting-edge problems and techniques, researchers from a wide range of fields will be able to gain insights for exploiting big heterogonous data in the life sciences through the concept of 'network of networks'.
Algorithmic Information Dynamics
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.
Networks of Networks in Biology
Introduces network inspired approaches for the analysis and integration of large, heterogeneous data sets in the life sciences.
Automata and Complexity
This book commemorates Eric Goles’s achievements in science and engineering. Eric Goles is one of the world leaders in the field of automata and complexity. His groundbreaking discoveries are in the theory and analysis of complex systems, particularly in the field of discrete systems dynamics such as neural networks, automata networks, majority networks, bootstrap percolation models, cellular automata, computational complexity theory, discrete mathematics, and theoretical computer science. Topics include cellular automata, complex networks, models of computation, expansive systems, sandpile automata, Penrose tilings, Boolean automata, models of infection, Fibonacci trees, dominos, reversible automata, and fungal automata. The chapters are authored by world leaders in computer science, physics, mathematics, and engineering. The book will be a pleasure to explore for readers from all walks of life, from undergraduate students to university professors, from mathematicians, computer scientists, and engineers to chemists and biologists.
Reachable Sets of Dynamic Systems
Reachable Sets of Dynamic Systems: Uncertainty, Sensitivity, and Complex Dynamics introduces differential inclusions, providing an overview as well as multiple examples of its interdisciplinary applications. The design of dynamic systems of any type is an important issue as is the influence of uncertainty in model parameters and model sensitivity. The possibility of calculating the reachable sets may be a powerful additional tool in such tasks. This book can help graduate students, researchers, and engineers working in the field of computer simulation and model building, in the calculation of reachable sets of dynamic models. Introduces methodologies and approaches to the modeling and simulation of dynamic systems Presents uncertainty treatment and model sensitivity are described, and interdisciplinary examples Explores applications of differential inclusions in modeling and simulation
Ethics of Life: freedom & diversity
A poetic and philosophical meditation on life and the importance of unusualness and diversity of life-forms, ideas, cultures, peoples and species. The book explores key themes of AI, freedom and free will, cooperation and competition, sacrifice and suffering. I have also created over 50 algorithmic artworks for the book. Life-forms are extraordinarily useful and unusual engines that make use of free energy to create complexity and information. We have many good reasons to value and protect the maximal compatible diversity of life-forms and species.
Uncertainty in Data Envelopment Analysis
Classical data envelopment analysis (DEA) models use crisp data to measure the inputs and outputs of a given system. In cases such as manufacturing systems, production processes, service systems, etc., the inputs and outputs may be complex and difficult to measure with classical DEA models. Crisp input and output data are fundamentally indispensable in the conventional DEA models. If these models contain complex uncertain data, then they will become more important and practical for decision makers.Uncertainty in Data Envelopment Analysis introduces methods to investigate uncertain data in DEA models, providing a deeper look into two types of uncertain DEA methods, fuzzy DEA and belief degree...
Computational Intelligence Techniques for Sustainable Supply Chain Management
Sustainable supply chain management involves integrating environmentally and financially viable practices into the complete supply chain lifecycle, from product design and development to material selection and sourcing, manufacturing, packaging, transportation, and distribution. A sustainable supply chain ensures balance between economic, social, and environmental performances – such as better assurance of human rights, ethical work practices, carbon footprint reduction, waste management, and resource efficiency. Computational Intelligence Techniques for Sustainable Supply Chain Management presents state-of-the-art computational intelligence techniques and applications for supply chain sus...
