Guides

Here are some tutorials to get started:

Getting Started

• Custom representation, variator and evaluator for OneMax: Getting Started with OneMax.

• Custom selectors: Making a Custom Selector.

• Custom algorithms: Making a Custom Algorithm.

• Collect runtime statistics with Watcher: Collect and Plotting Statistics.

Representations

• Genetic programming: Symbolic Regression with Genetic Programming

Advanced Tutorials

• Modify the behaviour of existing operators: Modifying Operators with the Interceptor Pattern

• Profile algorithm performance: Profiling Time and Memory Cost.

Learning from Documentation

The source code of EvoKit is heavily documented and typed. Because I too like to learn from documentation, I want to make it as easy as possible for you.

EvoKit’s building blocks derive the following classes:

• Operators derive Selector, Evaluator, and Variator.

• Algorithms derive Algorithm.

• Representations derive Individual; Population models a population.

You can find an example of how these work together in HomogeneousAlgorithm. The guides below give more detailed instructions.