EvoLudoLab: Fixation times on random regular graphs: Difference between revisions
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{{EvoLudoLab:Moran| | {{EvoLudoLab:Moran| | ||
options="--module Moran --run --delay 50 --view Statistics_-_Fixation_time --timestep 1 --popupdate B --popsize 81 --geometry r4 -- | options="--module Moran --run --delay 50 --view Statistics_-_Fixation_time --timestep 1 --popupdate B --popsize 81 --geometry r4 --init mutant 1,0 --fitness 1,2"| | ||
title=Fixation times on random regular graphs | | title=Fixation times on random regular graphs | | ||
doc=Even though fixation probabilities are the same on random regular graphs as on any other circulation, the corresponding fixation and absorption times can be vastly different. Because random regular graphs have a small diameter (every vertex can be reached with a few steps from every other one), fixation times remain comparable to those of the complete graph or unstructured populations. | doc=Even though fixation probabilities are the same on random regular graphs as on any other circulation, the corresponding fixation and absorption times can be vastly different. Because random regular graphs have a small diameter (every vertex can be reached with a few steps from every other one), fixation times remain comparable to those of the complete graph or unstructured populations. | ||
For the simulations, the population size is \(N=81\) with \(k=4\) neighbours, which results in a total of \(120\) links. 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. For reference, the analytical fixation and absorption times of the original Moran process are indicated by a dark red line.}} | For the simulations, the population size is \(N=81\) with \(k=4\) neighbours, which results in a total of \(120\) links. 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. For reference, the analytical fixation and absorption times of the original Moran process are indicated by a dark red line.}} | ||
Latest revision as of 13:32, 12 August 2024
| Color code: | Residents | Mutants |
|---|---|---|
| New resident | New mutant |
| Payoff code: | Residents | Mutants |
|---|
Fixation times on random regular graphs
Even though fixation probabilities are the same on random regular graphs as on any other circulation, the corresponding fixation and absorption times can be vastly different. Because random regular graphs have a small diameter (every vertex can be reached with a few steps from every other one), fixation times remain comparable to those of the complete graph or unstructured populations.
For the simulations, the population size is \(N=81\) with \(k=4\) neighbours, which results in a total of \(120\) links. 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. For reference, the analytical fixation and absorption times of the original Moran process are indicated by a dark red line.
Data views
| Snapshot of the spatial arrangement of strategies. | |
| 3D view of snapshot of the spatial arrangement of strategies. | |
| Time evolution of the strategy frequencies. | |
| Snapshot of the spatial distribution of payoffs. | |
| 3D view of snapshot of the spatial distribution of payoffs. | |
| Time evolution of average population payoff bounded by the minimum and maximum individual payoff. | |
| Snapshot of payoff distribution in population. | |
| Degree distribution in structured populations. | |
| Statistics of fixation probability for each vertex where the initial mutant arose. | |
| Statistics of conditional fixation times of residents and mutants as well as absorption time for each vertex where the initial mutant arose. | |
| Message log from engine. |
Game parameters
The list below describes only the few parameters related to the evolutionary dynamics of residents and mutants with fixed fitness (constant selection). Numerous other parameters are available to set population structures or update rules on the player as well as population level.
- --fitness <r,m>
- fitness of residents r and of mutants m.