Entropy Methods in Guided Self-Organisation
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CSIRO Digital Productivity, PO Box 76, Epping, NSW 1710, Australia
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Department of Computing, Macquarie University, E6A Level 3, Eastern Rd, Macquarie Park, NSW 2113, Australia
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School of Physics, University of Sydney, Physics Rd, Camperdown NSW 2050, Australia
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Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, A.P. 20-126, 01000 Mexico D.F., Mexico
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Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, A.P. 20-126, 01000 Mexico D.F., Mexico
*
Author to whom correspondence should be addressed.
Entropy 2014, 16(10), 5232-5241; https://doi.org/10.3390/e16105232
Received: 12 August 2014 / Revised: 22 September 2014 / Accepted: 29 September 2014 / Published: 9 October 2014
(This article belongs to the Special Issue Entropy Methods in Guided Self-Organization)
Self-organisation occurs in natural phenomena when a spontaneous increase in order is produced by the interactions of elements of a complex system. Thermodynamically, this increase must be offset by production of entropy which, broadly speaking, can be understood as a decrease in order. Ideally, self-organisation can be used to guide the system towards a desired regime or state, while "exporting" the entropy to the system's exterior. Thus, Guided Self-Organisation (GSO) attempts to harness the order-inducing potential of self-organisation for specific purposes. Not surprisingly, general methods developed to study entropy can also be applied to guided self-organisation. This special issue covers abroad diversity of GSO approaches which can be classified in three categories: information theory, intelligent agents, and collective behavior. The proposals make another step towards a unifying theory of GSO which promises to impact numerous research fields.
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Keywords:
entropy; guided self-organisation
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MDPI and ACS Style
Prokopenko, M.; Gershenson, C. Entropy Methods in Guided Self-Organisation. Entropy 2014, 16, 5232-5241. https://doi.org/10.3390/e16105232
AMA Style
Prokopenko M, Gershenson C. Entropy Methods in Guided Self-Organisation. Entropy. 2014; 16(10):5232-5241. https://doi.org/10.3390/e16105232
Chicago/Turabian StyleProkopenko, Mikhail; Gershenson, Carlos. 2014. "Entropy Methods in Guided Self-Organisation" Entropy 16, no. 10: 5232-5241. https://doi.org/10.3390/e16105232
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