EvoLudoLab: Fixation probabilities on the complete graph: Difference between revisions

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{{EvoLudoLab:Moran|
{{EvoLudoLab:Moran|
options="--game Moran --run --delay 50 --view Statistics_-_Fixation_probability --reportfreq 1 --popupdate B --popsize 81 --geometry c --initfreqs 0:1 --mutation 0 --basefit 1 --selection 1 --resident 1 --mutant 2"|
options="--module Moran --run --delay 50 --view Statistics_-_Fixation_probability --timestep 1 --popupdate B --popsize 81 --geometry c --init mutant 1,0 --fitness 1,2"|
title=Fixation probabilities on the complete graph|
title=Fixation probabilities on the complete graph|
doc=Since the complete graph is a circulation, the fixation probability of a mutant has to be the same irrespective of its initial location and must be identical to the one of the original Moran process in unstructured populations.
doc=Since the complete graph is a circulation, the fixation probability of a mutant has to be the same irrespective of its initial location and must be identical to the one of the original Moran process in unstructured populations.


For the simulations, the population size is \(N=81\) and hence \(3'240\) 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 probabilities of the original Moran process are indicated by a dark red line.}}
For the simulations, the population size is \(N=81\) and hence \(3'240\) 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 probabilities of the original Moran process are indicated by a dark red line.}}

Latest revision as of 13:29, 12 August 2024

Color code: Residents Mutants
New resident New mutant
Payoff code: Residents Mutants

Fixation probabilities on the complete graph

Since the complete graph is a circulation, the fixation probability of a mutant has to be the same irrespective of its initial location and must be identical to the one of the original Moran process in unstructured populations.

For the simulations, the population size is \(N=81\) and hence \(3'240\) 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 probabilities of the original Moran process are indicated by a dark red line.

Data views

Strategies - Structure

Snapshot of the spatial arrangement of strategies.

Strategies - Structure 3D

3D view of snapshot of the spatial arrangement of strategies.

Strategies - Mean

Time evolution of the strategy frequencies.

Fitness - Structure

Snapshot of the spatial distribution of payoffs.

Fitness - Structure 3D

3D view of snapshot of the spatial distribution of payoffs.

Fitness - Mean

Time evolution of average population payoff bounded by the minimum and maximum individual payoff.

Fitness - Histogram

Snapshot of payoff distribution in population.

Structure - Degree

Degree distribution in structured populations.

Statistics - Fixation probability

Statistics of fixation probability for each vertex where the initial mutant arose.

Statistics - Fixation times

Statistics of conditional fixation times of residents and mutants as well as absorption time for each vertex where the initial mutant arose.

Console log

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.