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A dynamic network population model with strategic link formation governed by individual preferences
- Source :
- Journal of Theoretical Biology
- Publication Year :
- 2013
- Publisher :
- Elsevier BV, 2013.
-
Abstract
- Historically most evolutionary models have considered infinite populations with no structure. Recently more realistic evolutionary models have been developed using evolutionary graph theory, which considered the evolution of structured populations. The structures involved in these populations are typically fixed, however, and real populations change their structure over both long and short time periods. In this paper we consider the dynamics of such a population structure. The timescales involved are sufficiently short that no individuals are born or die, but the links between individuals are in a constant state of flux, being actively governed by the preferences of the members of the population. The process is modelled using a Markov chain over the possible structures. We find that under the specified process the population evolves to a closed class of structures, and we show a method to find the stationary distribution on this class. We also consider some special cases of interest.
- Subjects :
- Statistics and Probability
Mathematical optimization
Dynamic network analysis
Population Dynamics
Population
Markov process
Models, Biological
General Biochemistry, Genetics and Molecular Biology
QH301
symbols.namesake
Evolutionary graph theory
Animals
Quantitative Biology::Populations and Evolution
Statistical physics
Evolutionary dynamics
education
Mathematics
education.field_of_study
Stationary distribution
General Immunology and Microbiology
Markov chain
Applied Mathematics
General Medicine
Markov Chains
Population model
Modeling and Simulation
symbols
General Agricultural and Biological Sciences
Subjects
Details
- ISSN :
- 00225193
- Volume :
- 335
- Database :
- OpenAIRE
- Journal :
- Journal of Theoretical Biology
- Accession number :
- edsair.doi.dedup.....3c35121d67b6fdefabad94bb5104abec
- Full Text :
- https://doi.org/10.1016/j.jtbi.2013.06.024