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The data of evolutionary biology have changed in a very radical way in recent years, the most significant input to this revolution being the advances made in developmental genetics. Another recent development is a noticeable shift away from extreme specialization in evolutionary biology. In this, we are perhaps to be reminded of George Gaylord Simpson's comments: "evolution is an incredibly complex but at the same time integrated and unitary process." The main objective of this book is to illustrate how natural adaptive systems evolve as a unity--with the particular objective of identifying and merging several special theories of evolution within the framework of a single general theory. The Evolution of Adaptive Systems provides an interdisciplinary overview of the general theory of evolution from the standpoint of the dynamic behavior of natural adaptive systems. The approach leads to a radically new fusion of the diverse disciplines of evolutionary biology, serving to resolve the considerable degree of conflict existing between different schools of contemporary thought. The book is a timely volume written by a natural historian with a broad view of biology The author draws examples from a large range of organisms from many different habitats and niches where interesting adaptations have evolved Probes deeply into mechanisms of evolution such as developmental genetics, morphogenesis, chromosome structure, and cladogenesis Clear definition of terms, with illustrations visualizing the main theoretical structures, and point-by-point summaries clearly stating the principal conclusions
Genetic algorithms are playing an increasingly important role in studies of complex adaptive systems, ranging from adaptive agents in economic theory to the use of machine learning techniques in the design of complex devices such as aircraft turbines and integrated circuits. Adaptation in Natural and Artificial Systems is the book that initiated this field of study, presenting the theoretical foundations and exploring applications. In its most familiar form, adaptation is a biological process, whereby organisms evolve by rearranging genetic material to survive in environments confronting them. In this now classic work, Holland presents a mathematical model that allows for the nonlinearity of such complex interactions. He demonstrates the model's universality by applying it to economics, physiological psychology, game theory, and artificial intelligence and then outlines the way in which this approach modifies the traditional views of mathematical genetics. Initially applying his concepts to simply defined artificial systems with limited numbers of parameters, Holland goes on to explore their use in the study of a wide range of complex, naturally occuring processes, concentrating on systems having multiple factors that interact in nonlinear ways. Along the way he accounts for major effects of coadaptation and coevolution: the emergence of building blocks, or schemata, that are recombined and passed on to succeeding generations to provide, innovations and improvements.
This book explores the universe and its subsystems from the three lenses of evolutionary (contingent), developmental (predictable), and complex (adaptive) processes at all scales. It draws from prolific experts within the academic disciplines of complexity science, physical science, information and computer science, theoretical and evo-devo biology, cosmology, astrobiology, evolutionary theory, developmental theory, and philosophy. The chapters come from a Satellite Meeting, "Evolution, Development and Complexity" (EDC) hosted at the Conference on Complex Systems, in Cancun, 2017. The contributions have been peer-reviewed and contributors from outside the conference were invited to submit chapters to ensure full coverage of the topics. This book explores many issues within the field of EDC such as the interaction of evolutionary stochasticity and developmental determinism in biological systems and what they might teach us about these twin processes in other complex systems. This text will appeal to students and researchers within the complex systems and EDC fields.
This graduate-level text focuses on the stability of adaptive systems, and offers a thorough understanding of the global stability properties essential to designing adaptive systems. Its self-contained, unified presentation of well-known results establishes the close connections between seemingly independent developments in the field. Prerequisites include a knowledge of linear algebra and differential equations, as well as a familiarity with basic concepts in linear systems theory. The first chapter sets the tone for the entire book, introducing basic concepts and tracing the evolution of the field from the 1960s through the 1980s. The first seven chapters are accessible to beginners, and the final four chapters are geared toward more advanced, research-oriented students. Problems ranging in complexity from relatively easy to quite difficult appear throughout the text. Topics include results in stability theory that emphasize incidents directly relevant to the study of adaptive systems; the stability properties of adaptive observers and controllers; the important concept of persistent excitation; the use of error models in systems analysis; areas of intense research activity; and five detailed case studies of systems in which adaptive control has proved successful
A novel, integrated approach to understanding long-term human history, viewing it as the long-term evolution of human information-processing. This title is also available as Open Access.
This book explores the universe and its subsystems from the three lenses of evolutionary (diversifying), developmental (converging), and complex (adaptive) processes at all scales. It draws from prolific experts within the academic disciplines of complexity science, physical science, information and computer science, theoretical and evo-devo biology, cosmology, astrobiology, evolutionary theory, developmental theory, and philosophy. The chapters come from a Satellite Meeting, "Evolution, Development and Complexity" (EDC) hosted at the Conference on Complex Systems, in Cancun, 2017. The contributions will be peer-reviewed and contributors from outside the conference will be invited to submit chapters to ensure full coverage of the topics. This book explores many issues within the field of EDC such as the interaction of evolutionary stochasticity and developmental determinism in biological systems and what they might teach us about these twin processes in other complex systems. This text will appeal to students and researchers within the complex systems and EDC fields. .
This book is a collection of essays exploring adaptive systems from many perspectives, ranging from computational applications to models of adaptation in living and social systems. The essays on computation discuss history, theory, applications, and possible threats of adaptive and evolving computations systems. The modeling chapters cover topics such as evolution in microbial populations, the evolution of cooperation, and how ideas about evolution relate to economics. The title Perspectives on Adaptation in Natural and Artificial Systems honors John Holland, whose 1975 Book, Adaptation in Natural and Artificial Systems has become a classic text for many disciplines in which adaptation play a central role. The essays brought together here were originally written to honor John Holland, and span most of the different areas touched by his wide-ranging and influential research career. The authors include some of the most prominent scientists in the fields of artificial intelligence evolutionary computation, and complex adaptive systems. Taken together, these essays present a broad modern picture of current research on adaptation as it relates to computers, living systems, society, and their complex interactions.
This book provides the first clear, comprehensive, and accessible account of complex adaptive social systems, by two of the field's leading authorities. Such systems--whether political parties, stock markets, or ant colonies--present some of the most intriguing theoretical and practical challenges confronting the social sciences. Engagingly written, and balancing technical detail with intuitive explanations, Complex Adaptive Systems focuses on the key tools and ideas that have emerged in the field since the mid-1990s, as well as the techniques needed to investigate such systems. It provides a detailed introduction to concepts such as emergence, self-organized criticality, automata, networks, diversity, adaptation, and feedback. It also demonstrates how complex adaptive systems can be explored using methods ranging from mathematics to computational models of adaptive agents. John Miller and Scott Page show how to combine ideas from economics, political science, biology, physics, and computer science to illuminate topics in organization, adaptation, decentralization, and robustness. They also demonstrate how the usual extremes used in modeling can be fruitfully transcended.
An overarching framework for comparing and steering complex adaptive systems is developed through understanding the mechanisms that generate their intricate signal/boundary hierarchies.
Based upon a conference held in May 1993, this book discusses the intersection of neurobiology, cognitive psychology and computational approaches to cognition.