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28 March 2024
 
  » arxiv » nlin.AO/0307015

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Methods and Techniques of Complex Systems Science: An Overview
Cosma Rohilla Shalizi ;
Date 9 Jul 2003
Subject Adaptation and Self-Organizing Systems; Chaotic Dynamics; Cellular Automata and Lattice Gases; Data Analysis, Statistics and Probability; Statistical Mechanics; Quantitative Methods | nlin.AO cond-mat.stat-mech nlin.CD nlin.CG physics.data-an q-bio.QM
AffiliationCenter for the Study of Complex Systems, University of Michigan
AbstractIn this chapter, I review the main methods and techniques of complex systems science. As a first step, I distinguish among the broad patterns which recur across complex systems, the topics complex systems science commonly studies, the tools employed, and the foundational science of complex systems. The focus of this chapter is overwhelmingly on the third heading, that of tools. These in turn divide, roughly, into tools for analyzing data, tools for constructing and evaluating models, and tools for measuring complexity. I discuss the principles of statistical learning and model selection; time series analysis; cellular automata; agent-based models; the evaluation of complex-systems models; information theory; and ways of measuring complexity. Throughout, I give only rough outlines of techniques, so that readers, confronted with new problems, will have a sense of which ones might be suitable, and which ones definitely are not.
Source arXiv, nlin.AO/0307015
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