%0 Book Section %B Guided Self-Organization: Inception %D 2014 %T Information Measures of Complexity, Emergence, Self-organization, Homeostasis, and Autopoiesis %A Nelson Fernández %A Carlos Maldonado %A Carlos Gershenson %E Mikhail Prokopenko %X

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.

%B Guided Self-Organization: Inception %I Springer %P 19-51 %G eng %U http://arxiv.org/abs/1304.1842 %0 Journal Article %J Artificial Life %D 2011 %T Complex Networks %A Carlos Gershenson %A Mikhail Prokopenko %X Introduction to the Special Issue on Complex Networks, Artificial Life journal. %B Artificial Life %I MIT Press %V 17 %P 259–261 %8 Fall %G eng %U http://arxiv.org/abs/1104.5538 %R 10.1162/artl_e_00037 %0 Book Section %B Self-Organization: Applied Multi-Agent Systems %D 2007 %T Self-organizing traffic lights: A realistic simulation %A Seung Bae Cools %A Carlos Gershenson %A Bart {D'Hooghe} %E Mikhail Prokopenko %X We have previously shown in an abstract simulation (Gershenson, 2005) that self-organizing traffic lights can improve greatly traffic flow for any density. In this paper, we extend these results to a realistic setting, implementing self-organizing traffic lights in an advanced traffic simulator using real data from a Brussels avenue. On average, for different traffic densities, travel waiting times are reduced by 50% compared to the current green wave method. %B Self-Organization: Applied Multi-Agent Systems %I Springer %P 41–49 %G eng %U http://arxiv.org/abs/nlin.AO/0610040 %& 3 %R 10.1007/978-1-84628-982-8_3