Investigating the Impact of Noise on GP Rule and GKL Rule on the Density Classification Task

This repository contains the code and data for the project titled "Investigating the Impact of Noise on GP Rule and GKL Rule on the Density Classification Task." The project aims to explore the effects of noise on the performance of the GP Rule and GKL Rule in the context of the density classification task using cellular automaton models.

Table of Contents

Introduction

Requirements

Introduction

In this project, we investigate the behavior of the GP Rule and GKL Rule under different levels of noise in the density classification task. The project utilizes the Cellpylib package in Python to implement and test the rules on 100,000 test cases. The goal is to evaluate the robustness and efficiency of the rules in the presence of noise and gain insights into the dynamics of cellular automata.

Requirements

To run the code in this repository, you need the following dependencies:

Python 3.9 - Jupter Notebook/Spider preferred and Cellpylib package