Information Measures of Complexity, Emergence, Self-organization, Homeostasis, and Autopoiesis

TitleInformation Measures of Complexity, Emergence, Self-organization, Homeostasis, and Autopoiesis
Publication TypeBook Chapter
Year of Publication2014
AuthorsFernández, N, Maldonado, C, Gershenson, C
EditorProkopenko, M
Book TitleGuided Self-Organization: Inception
Pagination19-51
PublisherSpringer
Abstract

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.

URLhttp://arxiv.org/abs/1304.1842
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