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A clear methodological and philosophical introduction to complexity theory as applied to urban and regional systems is given, together with a detailed series of modelling case studies compiled over the last couple of decades. Based on the new complex systems thinking, mathematical models are developed which attempt to simulate the evolution of towns, cities, and regions and the complicated co-evolutionary interaction there is both between and within them. The aim of these models is to help policy analysis and decision-making in urban and regional planning, energy policy, transport policy, and many other areas of service provision, infrastructure planning, and investment that are necessary for a successful society.
A clear methodological and philosophical introduction to complexity theory as applied to urban and regional systems is given, together with a detailed series of modelling case studies compiled over the last couple of decades. Based on the new complex systems thinking, mathematical models are developed which attempt to simulate the evolution of towns, cities, and regions and the complicated co-evolutionary interaction there is both between and within them. The aim of these models is to help policy analysis and decision-making in urban and regional planning, energy policy, transport policy, and many other areas of service provision, infrastructure planning, and investment that are necessary for a successful society.
The theory and practice of modeling cities and regions as complex, self-organizing systems, presenting widely used cellular automata-based models, theoretical discussions, and applications. Cities and regions grow (or occasionally decline), and continuously transform themselves as they do so. This book describes the theory and practice of modeling the spatial dynamics of urban growth and transformation. As cities are complex, adaptive, self-organizing systems, the most appropriate modeling framework is one based on the theory of self-organizing systems—an approach already used in such fields as physics and ecology. The book presents a series of models, most of them developed using cellular automata (CA), which are inherently spatial and computationally efficient. It also provides discussions of the theoretical, methodological, and philosophical issues that arise from the models. A case study illustrates the use of these models in urban and regional planning. Finally, the book presents a new, dynamic theory of urban spatial structure that emerges from the models and their applications. The models are primarily land use models, but the more advanced ones also show the dynamics of population and economic activities, and are integrated with models in other domains such as economics, demography, and transportation. The result is a rich and realistic representation of the spatial dynamics of a variety of urban phenomena. The book is unique in its coverage of both the general issues associated with complex self-organizing systems and the specifics of designing and implementing models of such systems.
This book integrates the theories of complex self-organizing systems with the rich body of discourse and literature developed in what might be called ‘social theory of cities and urbanism’. It uses techniques from dynamical complexity and synergetics to successfully tackle open social science questions.
Complex systems are usually difficult to design and control. There are several particular methods for coping with complexity, but there is no general approach to build complex systems. In this book I propose a methodology to aid engineers in the design and control of complex systems. This is based on the description of systems as self-organizing. Starting from the agent metaphor, the methodology proposes a conceptual framework and a series of steps to follow to find proper mechanisms that will promote elements to find solutions by actively interacting among themselves.
The Self-Organizing Economy In the last few years the concept of self-organizing systems—complex systems in which randomness and chaos seem spontaneously to evolve into unexpected order—has linked together researchers in many fields, from artificial intelligence to chemistry, from evolution to geology. Now leading economist Paul Krugman shows how principles that explain the growth of hurricanes and embryos can also explain the formation of cities and business cycles; how the same principles of “order from random growth” can explain the strangely simple rules that describe the sizes of earthquakes, meteorites, and metropolitan areas. Weaving together strands from many disciplines, from location theory to biology, The Self-Organizing Economy offers a surprising new view of how the economy structures itself in space and time.
The theory and practice of modeling cities and regions as complex, self-organizing systems, presenting widely used cellular automata-based models, theoretical discussions, and applications. Cities and regions grow (or occasionally decline), and continuously transform themselves as they do so. This book describes the theory and practice of modeling the spatial dynamics of urban growth and transformation. As cities are complex, adaptive, self-organizing systems, the most appropriate modeling framework is one based on the theory of self-organizing systems—an approach already used in such fields as physics and ecology. The book presents a series of models, most of them developed using cellular automata (CA), which are inherently spatial and computationally efficient. It also provides discussions of the theoretical, methodological, and philosophical issues that arise from the models. A case study illustrates the use of these models in urban and regional planning. Finally, the book presents a new, dynamic theory of urban spatial structure that emerges from the models and their applications. The models are primarily land use models, but the more advanced ones also show the dynamics of population and economic activities, and are integrated with models in other domains such as economics, demography, and transportation. The result is a rich and realistic representation of the spatial dynamics of a variety of urban phenomena. The book is unique in its coverage of both the general issues associated with complex self-organizing systems and the specifics of designing and implementing models of such systems.
In A New Philosophy of Society Manuel DeLanda offers a fascinating look at how the contemporary world is characterized by an extraordinary social complexity. Since most social entities, from small communities to large nation-states would disappear altogether if our cognitive abilities ceased to exist, DeLanda proposes a novel approach to social ontology that asserts the autonomy of social entities from the conceptions we have of them. He argues that Gilles Deleuze's theory of assemblages provides a framework in which sociologists and geographers studying social networks and regions can properly locate their work and fully elucidate the connections between them. Indeed, assemblage theory, as DeLanda argues, can be used to model any community, from interpersonal networks and institutional organizations, to central governments, cities and nation states.
To date, climate change adaptation and mitigation have been treated separately both in research and in the climate negotiations. However, a growing body of literature is now being developed that points to actual and potential synergies and trade-offs between responses to climate change and sustainability. This literature has evolved in a spontaneous way with diverse approaches and no common methodology to help practitioners explicitly plan for these synergies. This special issue of the Climate Policy journal addresses this gap between scientific knowledge and practitioners' needs by focussing on linkages between climate change and sustainable development at the level of conceptual framework and methods. In particular, the papers address in an integrated way local development options involving both adaptation and mitigation in order to promote resilience to climate change in human and natural systems. The special issue provides policy and methodological guidelines for linking local deveopment pathways with responses to climate change, based on collaboration between local practitioners, the public and scientists.
At a time of potentially radical changes in the ways in which humans interact with their environments - through financial, environmental and/or social crises - the raison d'être of spatial planning faces significant conceptual and empirical challenges. This Companion presents a multidimensional collection of critical narratives of conceptual challenges for spatial planning. The authors draw on various disciplinary traditions and theoretical frames to explore different ways of conceptualising spatial planning and the challenges it faces. Through problematising planning itself, the values which underpin planning and theory-practice relations, contributions make visible the limits of established planning theories and illustrate how, by thinking about new issues, or about issues in new ways, spatial planning might be advanced both theoretically and practically. There cannot be definitive answers to the conceptual challenges posed, but the authors in this collection provoke critical questions and debates over important issues for spatial planning and its future. A key question is not so much what planning theory is, but what might planning theory do in times of uncertainty and complexity. An underlying rationale is that planning theory and practice are intrinsically connected. The Companion is presented in three linked parts: issues which arise from an interactive understanding of the relations between planning ideas and the political-institutional contexts in which such ideas are put to work; key concepts in current theorising from mainly poststructuralist perspectives and what discussion on complexity may offer planning theory and practice.