Introduction

Welcome to the documentation of a model modeling a community of agents living in a common resource environment.

  1. Overview
  2. Quick Start
    1. Prerequisites
    2. Quick Run
    3. Important Command-line Arguments
    4. Interesting Scenarios to run

Overview

The documentation is separated into multiple parts:

  • Model Background — Describes the concept and literature of the model in a broader context.
  • Model Architecture — Shows the different (code) parts of the model and how they are connected.
  • Model Interaction — Explains how to interact with the model.
  • Model Parameters — Shows a listing of all parameters of the model per submodule.
  • Model Output — Gives an overview and explanation of the inner workings of all submodules producing about.

Quick Start

Prerequisites

  • The simulation assumes Python 3.6+, and requires the modules numpy, argparse, matplotlib and joblib to be installed.
    pip3 install numpy argparse matplotlib joblib
  • Download the code by cloning this repository.
    git clone "https://github.com/Leander-van-Boven/D28-Tragedy_of_the_Commons"

Quick Run

Since all parameters have a preset default value, the model can be started without changing any settings. The most basic command to use is therefore:

python3 sim.py run

This assumes that this command is run from the base folder of the repository.

Important Command-line Arguments

To change a the parameter of the model the --param [parameter]=[value] or -p [parameter]=[value] argument can be used

Refer to Parameters for a listing of all parameters per submodule

Interesting Scenarios to run

We included four scenarios that can be run by adding the --name argument (refer to Interaction). These are:

  • m.75s.05, which represents an initial agent SVO distribution with a mean of 0.75 and a standard deviation of 0.05. This configuration is identical to that found in Figure 6 of the report.
  • m.75s.15, which represents an initial agent SVO distribution with a mean of 0.75 and a standard deviation of 0.15. This configuration is identical to one found in Figure 5 of the report.
  • semi_stable, which shows a fluctuating agent distribution and resource pool but remains (almost always) stable.
  • resourcef_exp, which shows the behaviour of the exponential resource growth function.
  • resourcef_nroot, which shows the behaviour of the nth root resource growth function.
  • resourcef_log, which shows the behaviour of the logarithmic resource growth function.
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