Matjaž Perc (Author), Attila Szolnoki (Author)

Abstract

We study a stochastic predator-prey model on a square lattice, where each of the six species has two superior and two inferior partners. The invasion probabilities between species depend on the predator-prey pair and are supplemented by Gaussian noise. Conditions are identified that warrant the largest impact of noise on the evolutionary process, and the results of Monte Carlo simulations are qualitatively reproduced by a four-point cluster dynamical mean-field approximation. The observed noise-guided evolution is deeply routed in short-range spatial correlations, which is supported by simulations on other host lattice topologies. Our findings are conceptually related to the coherence resonance phenomenon in dynamical systems via the mechanism of threshold duality. We also show that the introduced concept of noise-guided evolution via the exploitation of threshold duality is not limited to predator-prey cyclical interactions, but may apply to models of evolutionary game theory as well, thus indicating its applicability in several different fields of research.

Keywords

dinamični sistemi;stohastični procesi;metode Monte Carlo;ciklični procesi;ciklične interakcije;prehranjevalna veriga;simulacije pretoka;evolucijski pojavi;dynamic systems;stochastic processes;cyclical interactions;evolutionary rules;flow simulations;Monte Carlo simulations;

Data

Language: English
Year of publishing:
Typology: 1.01 - Original Scientific Article
Organization: UM FNM - Faculty of Natural Sciences and Mathematics
UDC: 519.83
COBISS: 15669000 Link will open in a new window
ISSN: 1367-2630
Views: 1556
Downloads: 347
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Other data

Secondary language: Slovenian
Secondary keywords: dinamični sistemi;stohastični procesi;metode Monte Carlo;ciklični procesi;ciklične interakcije;prehranjevalna veriga;simulacije pretoka;evolucijski pojavi;
URN: URN:SI:UM:
Type (COBISS): Scientific work
Pages: str. 1-13
Volume: ǂVol. ǂ9
Issue: 267
Chronology: Avg. 2007
DOI: 10.1088/1367-2630/9/8/267
ID: 8724133