Noise-guided evolution within cyclical interactions

By Matjaz Perc, Attila Szolnoki. 2007

107 citations recorded by the source corpus.

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.

Subfields: Computer Networks and Communications, Condensed Matter Physics, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/cd25cb0502ef2bb53fa5666bebbe107ae4401139

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In Computer Networks and Communications

  1. Matjaz Perc
  2. Attila Szolnoki
  3. Mauro Mobilia

In Condensed Matter Physics

  1. Matjaz Perc
  2. Mauro Mobilia

In Statistical and Nonlinear Physics

  1. Matjaz Perc
  2. Attila Szolnoki
  3. Mauro Mobilia
  4. Bartosz Szczesny
  5. Alastair M. Rucklidge
  6. Luo-Luo Jiang

Citations in the corpus