One of the central challenges of computer science is to use a computer to do what needs to be done without telling it/knowing the specific process. Genetic programming (GP) addresses this challenge by providing a method for automatically creating a working computer program from a high-level statement of a specific task. GP achieves this goal by genetically breeding a population of computer programs using the principles of Darwinian natural selection and biologically inspired operations.

This talk will start with an overview of GP principles, including representation, operators, search mechanisms and the evolutionary process. The talk will then discuss the most popular applications of GP with a focus on the evolved "models" and "generalisation" on symbolic regression and mathematical modelling, feature selection and construction, and image recognition. At the end of this talk, I will discuss the practice and challenges of EC research in the ECRG group.