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Complex landscapes of spatial interaction
Abstract. How complex is the spatial economy? Some apostles of complexity argue that complex behaviour can arise in any system consisting of a largish number of intelligent, adaptive agents interacting on the basis of local information only. This paper examines several features of such dynamic systems, including path-dependence, emergence and self-organization. It goes on to explore their importance for the spatial sciences. Because space scales can change abruptly from local to global, strongly-interactive spatial economies sometimes exhibit astonishing collective properties, emergent features which are lawful in their own right. Segregation, self-similarity and the rank-size rule are familiar examples. To understand how collective order arises from seemingly random fluctuations, we must note how agents choose to interact with other agents and with their environment. We must synthesize rather than analyse. In the paper, self-organization is explored in a variety of contexts, including Schelling's model of neighborhood segregation and some work with cellular automata that has sharpened our insights into the collective synthesis of agents' interactions. Power laws are widely observed. A new way of doing social science – agent-based simulation – offers powerful new insights. It seems likely to revolutionize our field, along with the whole of the social sciences. Some of the current research underway in this area is discussed. “Truth is much too complicated to allow anything but approximations.” John von Neumann
Complex landscapes of spatial interaction
Abstract. How complex is the spatial economy? Some apostles of complexity argue that complex behaviour can arise in any system consisting of a largish number of intelligent, adaptive agents interacting on the basis of local information only. This paper examines several features of such dynamic systems, including path-dependence, emergence and self-organization. It goes on to explore their importance for the spatial sciences. Because space scales can change abruptly from local to global, strongly-interactive spatial economies sometimes exhibit astonishing collective properties, emergent features which are lawful in their own right. Segregation, self-similarity and the rank-size rule are familiar examples. To understand how collective order arises from seemingly random fluctuations, we must note how agents choose to interact with other agents and with their environment. We must synthesize rather than analyse. In the paper, self-organization is explored in a variety of contexts, including Schelling's model of neighborhood segregation and some work with cellular automata that has sharpened our insights into the collective synthesis of agents' interactions. Power laws are widely observed. A new way of doing social science – agent-based simulation – offers powerful new insights. It seems likely to revolutionize our field, along with the whole of the social sciences. Some of the current research underway in this area is discussed. “Truth is much too complicated to allow anything but approximations.” John von Neumann
Complex landscapes of spatial interaction
Batten, David F. (author)
2001
Article (Journal)
English
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