EvoLudoLab: Fixation times on the star graph

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Revision as of 20:49, 17 December 2018 by Hauert (talk | contribs)
Color code: Residents Mutants
New resident New mutant
Payoff code: Residents Mutants

Fixation times on the star graph

Note that the fixation times are not the same for all vertices. In particular, if the mutant is placed in the hub (vertex \(0\)), it almost certainly gets wiped out in the very first update. For symmetry reasons, all other vertices have the same fixation times. The fixation times on the star graph are orders of magnitude longer than for the original Moran process, which is shown as a dark red line for reference.

For the simulations, the population size is \(N=96\). The fitness of residents is set to \(1\) and that of mutants to \(2\). Note that the fixation time for residents is essentially zero for the hub but for mutants it is the same as for all other vertices. The difference is only that the chances for the latter to happen are very small and is also reflected in the very small absorption time for the hub.

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.
--init <r,m>
initial frequencies of residents r and mutants m. Frequencies that do not add up to 100% are scaled accordingly.
--inittype <type>
type of initial configuration:
frequency
random distribution with given frequency
uniform
uniform random distribution
monomorphic
monomorphic initialization
mutant
single mutant in homogeneous population of another type. Mutant and resident types are determined by the types with the lowest and highest frequency, respectively (see option --init).
stripes
stripes of traits
kaleidoscopes
(optional) configurations that produce evolutionary kaleidoscopes for deterministic updates (players and population). Not available for all types of games.