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
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
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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