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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/309

Title: Efficiency and persistence in models of adaptation
Authors: D'Hulst, R
Rodgers, GJ
Keywords: Statistical mechanics
Disordered systems and neural networks
Publication Date: 2001
Publisher: Elsevier Science
Citation: Physica A, 324(1): 323-329(7), Jun 2003
Abstract: A cut-and-paste model which mimics a trial-and-error process of adaptation is introduced and solved. The model, which can be thought of as a diffusion process with memory, is characterized by two properties, efficiency and persistence. We establish a link between these properties and determine two transitions for each property, a percolation transition and a depinning transition. If the adaptation process is iterated, the antipersistent state becomes an attractor of the dynamics. Extensions to higher dimensions are briefly discussed.
URI: http://www.ingentaconnect.com/content/els/03784371
http://bura.brunel.ac.uk/handle/2438/309
Appears in Collections:School of Information Systems, Computing and Mathematics Research Papers
Mathematical Physics
Mathematical Science

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