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Concepts used in the scientific study of complex systems have become so widespread that their use and abuse has led to ambiguity and confusion in their meaning. In this paper we use information theory to provide abstract and concise measures of complexity, emergence, self-organization, and homeostasis. The purpose is to clarify the meaning of these concepts with the aid of the proposed formal measures. In a simplified version of the measures (focusing on the information produced by a system), emergence becomes the opposite of self-organization, while complexity represents their balance. Homeostasis can be seen as a measure of the stability of the system. We use computational experiments on random Boolean networks and elementary cellular automata to illustrate our measures at multiple scales.

We comment on Alan Turing's celebrated paper "The Chemical Basis of Morphogenesis" published in 1952 in the "Philosophical Transactions of the Royal Society of London". It is a typical example of a pioneering and inspired work in the domain of mathematical modelling.

We comment on Alan Turing's celebrated paper "The Chemical Basis of Morphogenesis" published in 1952 in the "Philosophical Transactions of the Royal Society of London". It is a typical example of a pioneering and inspired work in the domain of mathematical modelling.

We comment on Alan Turing's celebrated paper "The Chemical Basis of Morphogenesis" published in 1952 in the "Philosophical Transactions of the Royal Society of London". It is a typical example of a pioneering and inspired work in the domain of mathematical modelling.

We comment on Alan Turing's celebrated paper "The Chemical Basis of Morphogenesis" published in 1952 in the "Philosophical Transactions of the Royal Society of London". It is a typical example of a pioneering and inspired work in the domain of mathematical modelling.

Stuart Kauffman here presents a brilliant new paradigm for evolutionary biology, one that extends the basic concepts of Darwinian evolution to accommodate recent findings and perspectives from the fields of biology, physics, chemistry and mathematics. The book drives to the heart of the exciting debate on the origins of life and maintenance of order in complex biological systems. It focuses on the concept of the spontaneous emergence of order that is widely observed throughout nature Kauffman argues that self-organization plays an important role in the Darwinian process of natural selection. Yet until now no systematic effort has been made to incorporate the concept of self-organization into evolutionary theory. The construction requirements which permit complex systems to adapt are poorly understood, as is the extent to which selection itself can yield systems able to adapt more successfully. This book explores these themes. It shows how complex systems, contrary to expectations, can spontaneously exhibit stunning degrees of order, and how this order, in turn, is essential for understanding the emergence and development of life on Earth. Topics include the new biotechnology of applied molecular evolution, with its important implications for developing new drugs and vaccines; the balance between order and chaos observed in many naturally occurring systems; new insights concerning the predictive power of statistical mechanics in biology; and other major issues. Indeed, the approaches investigated here may prove to be the new center around which biological science itself will evolve. The work is written for all those interested in the cutting edge of research in the life sciences.

Stuart Kauffman here presents a brilliant new paradigm for evolutionary biology, one that extends the basic concepts of Darwinian evolution to accommodate recent findings and perspectives from the fields of biology, physics, chemistry and mathematics. The book drives to the heart of the exciting debate on the origins of life and maintenance of order in complex biological systems. It focuses on the concept of the spontaneous emergence of order that is widely observed throughout nature Kauffman argues that self-organization plays an important role in the Darwinian process of natural selection. Yet until now no systematic effort has been made to incorporate the concept of self-organization into evolutionary theory. The construction requirements which permit complex systems to adapt are poorly understood, as is the extent to which selection itself can yield systems able to adapt more successfully. This book explores these themes. It shows how complex systems, contrary to expectations, can spontaneously exhibit stunning degrees of order, and how this order, in turn, is essential for understanding the emergence and development of life on Earth. Topics include the new biotechnology of applied molecular evolution, with its important implications for developing new drugs and vaccines; the balance between order and chaos observed in many naturally occurring systems; new insights concerning the predictive power of statistical mechanics in biology; and other major issues. Indeed, the approaches investigated here may prove to be the new center around which biological science itself will evolve. The work is written for all those interested in the cutting edge of research in the life sciences.

Stuart Kauffman here presents a brilliant new paradigm for evolutionary biology, one that extends the basic concepts of Darwinian evolution to accommodate recent findings and perspectives from the fields of biology, physics, chemistry and mathematics. The book drives to the heart of the exciting debate on the origins of life and maintenance of order in complex biological systems. It focuses on the concept of the spontaneous emergence of order that is widely observed throughout nature Kauffman argues that self-organization plays an important role in the Darwinian process of natural selection. Yet until now no systematic effort has been made to incorporate the concept of self-organization into evolutionary theory. The construction requirements which permit complex systems to adapt are poorly understood, as is the extent to which selection itself can yield systems able to adapt more successfully. This book explores these themes. It shows how complex systems, contrary to expectations, can spontaneously exhibit stunning degrees of order, and how this order, in turn, is essential for understanding the emergence and development of life on Earth. Topics include the new biotechnology of applied molecular evolution, with its important implications for developing new drugs and vaccines; the balance between order and chaos observed in many naturally occurring systems; new insights concerning the predictive power of statistical mechanics in biology; and other major issues. Indeed, the approaches investigated here may prove to be the new center around which biological science itself will evolve. The work is written for all those interested in the cutting edge of research in the life sciences.

The Department of Defense (DoD) spends at least 60% of its budget for the acquisition and sustainment of new material capability and services. The DoDs track record with regard to maximizing value from this investment has been poor, to say the least, and warrants a more in-depth understanding of the root cause of the problem. The lack of a successful integrated network approach to the problem of poor program performance is evident in the many significant cost and schedule program overruns and the failure of legislation and policy emanating from initiatives such as the Packard Commission study, Goldwater-Nichols Legislation, and more recently, the Better Buying Power initiative.

Focusing upon the central problems of effective community practice in town and country areas, the four speeches in this collection emphasize some key analytical notions in what has been termed an interactional or activity field conception of community. Among the ideas emphasized are the complexity/integration and the coordination/integration of community structure and the coordinating association and the service agency as key organizations in community development. The four papers are titled and sub-titled as follows: (1) "Community Development: Dialectics in Practice and Theory" (Technology and Community Structure; Community Structures and Processes; Multiple Fields and Goal-Structure Interaction; Community Coordination and Development Models); (2) "Two Basic Structures in the Development of the Modern Community" (Community Coordinating Structures; The Service Agency; Basic Structures, Development Models, and Goal Attainment); (3) "The Multi-County Area as a Community" (The Social Field Perspective; The Emerging Rural-Urban Locality; Two or More Fields in a Multicounty Area; Type of Field and Nature of Integration; Integration of the Multicounty Area); (4) "The Community Association and Comprehensive Development" (Structural Dimensions; New Structures and Projects; The Coordination of Organization; Use of External Resources; Local Development and Community Theory). (JC)

Focusing upon the central problems of effective community practice in town and country areas, the four speeches in this collection emphasize some key analytical notions in what has been termed an interactional or activity field conception of community. Among the ideas emphasized are the complexity/integration and the coordination/integration of community structure and the coordinating association and the service agency as key organizations in community development. The four papers are titled and sub-titled as follows: (1) "Community Development: Dialectics in Practice and Theory" (Technology and Community Structure; Community Structures and Processes; Multiple Fields and Goal-Structure Interaction; Community Coordination and Development Models); (2) "Two Basic Structures in the Development of the Modern Community" (Community Coordinating Structures; The Service Agency; Basic Structures, Development Models, and Goal Attainment); (3) "The Multi-County Area as a Community" (The Social Field Perspective; The Emerging Rural-Urban Locality; Two or More Fields in a Multicounty Area; Type of Field and Nature of Integration; Integration of the Multicounty Area); (4) "The Community Association and Comprehensive Development" (Structural Dimensions; New Structures and Projects; The Coordination of Organization; Use of External Resources; Local Development and Community Theory). (JC)

Intrinsic computation refers to how dynamical systems store, structure, and transform historical and spatial information. By graphing a measure of structural complexity against a measure of randomness, complexity-entropy diagrams display the range and different kinds of intrinsic computation across an entire class of system. Here, we use complexity-entropy diagrams to analyze intrinsic computation in a broad array of deterministic nonlinear and linear stochastic processes, including maps of the interval, cellular automata and Ising spin systems in one and two dimensions, Markov chains, and probabilistic minimal finite-state machines. Since complexity-entropy diagrams are a function only of observed configurations, they can be used to compare systems without reference to system coordinates or parameters. It has been known for some time that in special cases complexity-entropy diagrams reveal that high degrees of information processing are associated with phase transitions in the underlying process space, the so-called ``edge of chaos''. Generally, though, complexity-entropy diagrams differ substantially in character, demonstrating a genuine diversity of distinct kinds of intrinsic computation.

Intrinsic computation refers to how dynamical systems store, structure, and transform historical and spatial information. By graphing a measure of structural complexity against a measure of randomness, complexity-entropy diagrams display the range and different kinds of intrinsic computation across an entire class of system. Here, we use complexity-entropy diagrams to analyze intrinsic computation in a broad array of deterministic nonlinear and linear stochastic processes, including maps of the interval, cellular automata and Ising spin systems in one and two dimensions, Markov chains, and probabilistic minimal finite-state machines. Since complexity-entropy diagrams are a function only of observed configurations, they can be used to compare systems without reference to system coordinates or parameters. It has been known for some time that in special cases complexity-entropy diagrams reveal that high degrees of information processing are associated with phase transitions in the underlying process space, the so-called ``edge of chaos''. Generally, though, complexity-entropy diagrams differ substantially in character, demonstrating a genuine diversity of distinct kinds of intrinsic computation.

This chapter reviews measures of emergence, self-organization, complexity, homeostasis, and autopoiesis based on information theory. These measures are derived from proposed axioms and tested in two case studies: random Boolean networks and an Arctic lake ecosystem. Emergence is defined as the information produced by a system or process. Self-organization is defined as the opposite of emergence, while complexity is defined as the balance between emergence and self-organization. Homeostasis reflects the stability of a system. Autopoiesis is defined as the ratio between the complexity of a system and the complexity of its environment. The proposed measures can be applied at different scales, which can be studied with multi-scale profiles.

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Perma.cc archive of https://www.jstor.org/stable/pdf/2640328.pdf?casa_token=Mqy9tv2HBSYAAAAA:etnQfkmSJasA3_TR010ApBZtKTQ_1hCFiihMcgTQ5fsE3Q8gZDOVM4Yi5el5UZheKsw5oJkBmcGB--8ulm4RUGHjapQDkUE8KgrrjfACCljj2H05RQ created on 2021-11-04 00:16:05+00:00.