Explainable artificial intelligence (XAI) has received great interest in the recent decade, due
to its importance in critical application domains, such as self-driving cars, law, and …

Evolution does not require DNA, or even living organisms. In computer science, the field
known as' evolutionary computation'uses evolution as an algorithmic tool, implementing …

This is the second edition of our 2003 book. It is primarily a book for lecturers and graduate
and undergraduate students. To this group the book offers a thorough introduction to …

The latest book on Genetic Programming, Poli, Langdon and McPhee's (with contributions
from John R. Koza) A Field Guide to Genetic Programming represents an exciting landmark …

Genetic programming (GP), one of the most advanced forms of evolutionary computation,
has been highly successful as a technique for getting computers to automatically solve …

This paper describes a new hybrid regression method that combines the best features of
conventional numerical regression techniques with the genetic programming symbolic …

This paper presents a novel approach to generate data-driven regression models that not
only give reliable prediction of the observed data but also have smoother response surfaces …

Examines measures of diversity in genetic programming. The goal is to understand the
importance of such measures and their relationship with fitness. Diversity methods and …

This paper presents GPLAB, a genetic programming toolbox for MATLAB. Besides most of
the features traditionally used in genetic programming, it also implements two techniques …

This study investigates the use of multiobjective techniques in genetic programming (GP) in
order to evolve compact programs and to reduce the effects caused by bloating. The …