The code numerically solves the equation. In addition, it graphs and analyses the results.

The main goal of the code is to numerically solve the set of differential equations that describe the replicator-mutator equation (see eqs 2 and 3) for the Traveler's Dilemma (see Figure 1). The replicator-mutator equation is the generalizaton of the replicator dynamics. When no mutations are allowed ( $q=0$ ), the replicator-mutator equation is equivalent to the replicator dynamics. The main parameters to explore are R (reward value) and q (mutation strength).

Note: q is also named Mu in the code.

-To solve the replicator-mutator equations and obtain the data: julia scripts/SolveRepMut.jl R Mu

-To solve the replicator dynamics system and obtain the data: julia scripts/SolveRepMut.jl R 0

or julia scripts/SolveRep.jl R

-To graph the solution of the replicator-mutator equations as a timeseries: julia scripts/GraphRepMut.jl R Mu

-To graph the solution of the replicator dynamics as a timeseries: julia scripts/GraphRepMut.jl R 0

or julia scripts/GraphRep.jl R

-To measure the quantifiers to characterise the solution of the replicator-mutator equation: julia scripts/Quantifiers.jl R Mu

-To measure the quantifiers to characterise the solution of the replicator dynamics: julia scripts/Quantifiers.jl R 0

To run the code in batch.

-To set the parameters to be explored: cluster_scripts/ParametersToRun.jl (it returns the file Parameters.txt)

-To run the scripts to solve and graph the system for the parameters set in Parameters.txt: bash cluster_scripts/RunSbatchs.sh

-To run Quantifiers.jl for the entire parameter set: sbatch cluster_scripts/SbatchCompact.sh

-To graph the quantifiers contour plot for the entire parameter set: julia process_cluster/ClusterGraphData

This code base is using the Julia Language and DrWatson to make a reproducible scientific project named

Replicator_Mutator_Eq

It is authored by Maria Alejandra Ramirez.

To (locally) reproduce this project, do the following:

0. Download this code base. Notice that raw data are typically not included in the git-history and may need to be downloaded independently.
1. Open a Julia console and do:

   julia> using Pkg
   julia> Pkg.add("DrWatson") # install globally, for using `quickactivate`
   julia> Pkg.activate("path/to/this/project")
   julia> Pkg.instantiate()
   

This will install all necessary packages for you to be able to run the scripts and everything should work out of the box, including correctly finding local paths.