EvoLudoLab: Moran process on the cycle graph

Color code:	Residents	Mutants
	New resident	New mutant

Payoff code:	Residents	Mutants

Evolutionary dynamics on the complete graph

For the linear graph (or 1D lattice) the invasion process of a mutant can be easily illustrated over time by stacking subsequent snapshots of the population state. Each row indicates the population state at a particular time such that the most recent state is at the top and and towards the bottom of the figure are population states in the increasingly distant past.

In this graphical representation it is easy to see that mutants invade by forming a single, growing cluster. Due to the structure of the graph, there will always be at most two clusters, one of residents and another of mutants. Because of the limited opportunities for mutants to spread, the invasion process is significantly slower than on the complete graph or in unstructured populations.

For the simulations, the population size is \(N=100\). 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. Typically it takes around \(120\) generations for the mutant to reach fixation (as compared to around \(12\) on the complete graph).

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.