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| Title: | Efficiency and persistence in models of adaptation |
| Authors: | D'Hulst, R Rodgers, G J |
| Keywords: | Statistical Mechanics Disordered Systems and Neural Networks |
| Publication Date: | 2001 |
| Publisher: | Elsevier Science |
| Citation: | Physica A, Volume 324, Number 1, 1 June 2003, pp. 323-329(7) |
| 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: | Mathematics School of Information Systems, Computing and Mathematics Research Papers Mathematical Physics
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