860
edits
EvoLudoLab: Moran process on random regular graphs: Difference between revisions
From EvoLudo
EvoLudoLab: Moran process on random regular graphs (view source)
Revision as of 21:21, 17 December 2018
, 17 December 2018no edit summary
(Created page with "{{EvoLudoLab:Moran| options="--game Moran --run --delay 100 --view Strategies_-_Structure --reportfreq 1 --popupdate B --popsize 1000 --geometry r3 --initfreqs 0:1 --mutation...") |
No edit summary |
||
| Line 1: | Line 1: | ||
{{EvoLudoLab:Moran| | {{EvoLudoLab:Moran| | ||
options="--game Moran --run --delay 100 --view Strategies_-_Structure --reportfreq 1 --popupdate B --popsize 1000 --geometry r3 --initfreqs 0 | options="--game Moran --run --delay 100 --view Strategies_-_Structure --reportfreq 1 --popupdate B --popsize 1000 --geometry r3 --initfreqs 1:0 --mutation 0 --basefit 1 --selection 1 --fitness 1:2"| | ||
title=Evolutionary dynamics on the complete graph| | title=Evolutionary dynamics on the complete graph| | ||
doc=On random regular graphs any vertex can be reached from any other one in relatively few steps. Consequentially, the invasion process of mutants is similar to the complete graph (or even unstructured populations) and no characteristic invasion patterns emerge, with the only difference that it takes a little longer. | doc=On random regular graphs any vertex can be reached from any other one in relatively few steps. Consequentially, the invasion process of mutants is similar to the complete graph (or even unstructured populations) and no characteristic invasion patterns emerge, with the only difference that it takes a little longer. | ||
For the simulations, the population size is \(N=1000\) and every vertex has \(k=3\) neighbours. The fitness of residents is set to \(1\) and that of mutants to \(2\). Thus, a single mutant has approximately a \(50\%\) chance to take over the population. Typically it takes around \(40\) generations for the mutant to reach fixation, which is around twice as long as in an unstructured population.}} | For the simulations, the population size is \(N=1000\) and every vertex has \(k=3\) neighbours. The fitness of residents is set to \(1\) and that of mutants to \(2\). Thus, a single mutant has approximately a \(50\%\) chance to take over the population. Typically it takes around \(40\) generations for the mutant to reach fixation, which is around twice as long as in an unstructured population.}} | ||
