Relating Complexities for the Reflexive Study of Complex Systems
Abstract
Several approaches and corresponding definitions of complexity have been developed in different fields. Urban systems are the archetype of complex socio-technical systems concerned with these different viewpoints. We suggest in this chapter some links between three types of complexity, namely emergence, computational complexity and informational complexity. We discuss the implication of these links on the necessity of reflexivity to produce a knowledge of the complex, and how this connects to the interdisciplinary of approaches in particular for socio-technical systems. We finally synthesize this positioning as a proposal of an epistemological framework called applied perspectivism, and discuss the implications for the study of urban systems.
Domains
Humanities and Social Sciences Geography Computer Science [cs] Multiagent Systems [cs.MA] Computer Science [cs] Discrete Mathematics [cs.DM] Statistics [stat] Machine Learning [stat.ML] Nonlinear Sciences [physics] Cellular Automata and Lattice Gases [nlin.CG] Nonlinear Sciences [physics] Chaotic Dynamics [nlin.CD] Nonlinear Sciences [physics] Adaptation and Self-Organizing Systems [nlin.AO] Quantitative Finance [q-fin] Computational Finance [q-fin.CP] Environmental Sciences Biodiversity and Ecology
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BookUrbanization_ChapterRaimbault_Complexities_v2.pdf (124.66 Ko)
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