Genetic Programming Toolbox for MATLAB

A framework for building genetic programming (GP) models.

The framework contains:

• The representation of genetic programs (parse trees)
• Genetic operators including natural selection, reproduction, and mutation
• An easy-to-use programming framework to build and train your GP models
• A template system to specify the nodes allowed for each type.
• A genetic algorithm optimization framework (you can choose not to use GP).

What is Genetic Programming?

Genetic programming (GP) is an extension of genetic algorithms. GP encodes the parameters into a parse tree rather than a chromosome, which is normally represented as a string. A parse tree is a representation of a string's syntactic structure as described by some context-free grammar. It starts from a population of randomly generated programs, then tries to fit for a particular task by applying genetic operators iteratively over a number of generations. Finally, the optimization algorithm returns the best model in the population.

Getting Started

1. Clone the project into your project

   git clone https://github.com/RapDoodle/Genetic-Programming-MATLAB.git ./gp

2. Add the toolbox to your MATLAB path

   addpath(genpath('./gp'));

3. Start coding.

Documentation and Examples

You can find more documentation and examples in the documentation folder.

Table of Contents

1. Introduction.
2. Components
   1. Node
   2. Variable
   3. Signal
   4. Template
   5. GAMember
   6. GPMember
   7. GAModel
   8. GPModel
3. Examples
   1. Genetic programming based trading bot

Note: The development documentation is not available at the moment. But the code does contain an extensive amount of comments.

License

This project is licensed under the MIT license. Copyright (c) 2022 Bohui WU.