This repository contains various agent-based models implemented in different environments.
The Tutorial2_Maxtend class is designed to be implemented in the greater HAL (Hybrid Automata Library) environment. This class introduces a third agent type and allows for non-spatial interactions between concurrent populations via Lotka–Volterra dynamics.
The ParamExplorer class is used to design and run parameter sweeps using the Tutorial2_Maxtend implementation of HAL.
The graphing_data Python file is used to analyze and graph the data generated with HAL. Example outputs are given in the HAL results directory.
A custom Python agent-based model, designed to handle an arbitrary number of agent types, as well as simulating diffusion-based interactions via Gaussian kernel convolution.
My first agent-based model, created in RStudio. Here, agents only interact by spatial exclusion, and each spot on the grid can support an arbitrary number of agents. Agents are also able to move in every cardinal direction.