EvoLudoLab: Fixation probabilities on the linear chain graph

From EvoLudo
Revision as of 14:34, 12 August 2024 by Hauert (talk | contribs)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Color code: Residents Mutants
New resident New mutant
Payoff code: Residents Mutants

Fixation probabilities on the linear chain graph

The fixation probability is zero for all vertices except for the root (vertex \(0\)) for which it is one.

For the simulations, the population size is \(N=100\), the fitness of residents is set to \(1\) and that of mutants to \(2\). As a reference, the fixation probabilities for the original Moran process are indicated by a dark red line at approximately \(50\%\) for these settings.

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.