EvoLudoLab: Fixation times on the cycle graph

From EvoLudo
Revision as of 23:02, 11 October 2023 by Hauert (talk | contribs)
Color code: Residents Mutants
New resident New mutant
Payoff code: Residents Mutants

Fixation times on the cycle graph

Even though fixation probabilities are the same on the cycle graph as on any other circulation, the corresponding fixation and absorption times can be vastly different. The diameter of cycle graphs ( the average minimal number of steps to reach any vertex from any other one) scales with \(N\) and hence fixation times are long - possibly the longest on any circulation with undirected links.

For the simulations, the population size is \(N=81\) with \(k=2\) neighbours and hence also a total of \(81\) 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

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.