Learning Outcomes

The aim of this module is to give an introduction to the main techniques of evolutionary computation and genetic programming.

After completing this module, students will be expected to be able to:

1. Demonstrate an understanding of evolutionary algorithms and their relationships.
2. Demonstrate an understanding of genetic programming and its relationship with other evolutionary algorithms.
3. Categorise typical genetic programming application domains and associate these with good genetic programming techniques.
4. Determine the right parameter settings and specialise existing genetic programming operators, representations and fitness functions for specific applications.

Outline Syllabus

Evolution in Nature
Evolution Strategies
Genetic Algorithms
The basics of Genetic Programming (GP)
Fitness functions in GP
Advanced Representations
Code growth and methods to control it
Applications of GP.
Criteria for human-competitive machine intelligence and review of GP's human-competitive results
Advanced techniques and tricks of the trade.