The coauthorship and coeditorship relations as recorded in the genetic programming bibliography provide a quantitative view of the GP community. Eigen analysis is used to find the ...
William B. Langdon, Riccardo Poli, Wolfgang Banzha...
There are various representations for encoding graph structures, such as artificial neural networks (ANNs) and circuits, each with its own strengths and weaknesses. Here we analyz...
New Particle Swarm Optimization (PSO) methods for dynamic and noisy function optimization are studied in this paper. The new methods are based on the hierarchical PSO (H-PSO) and a...
Abstract. Bedau et al.'s statistical classification system for long-term evolutionary dynamics provides a test for open-ended evolution. Making this test more rigorous, and pa...
Abstract. Too much information kills information. This common statement applies to huge databases, where state of the art search engines may retrieve hundreds of very similar docum...
Yann Landrin-Schweitzer, Pierre Collet, Evelyne Lu...
Genetic programming (GP) extends traditional genetic algorithms to automatically induce computer programs. GP has been applied in a wide range of applications such as software ree...
A novel method for solving ordinary and partial differential equations, based on grammatical evolution is presented. The method forms generations of trial solutions expressed in an...
This paper presents a Genetic Programming (GP) approach to the design of Mathematical Morphology (MM) algorithms for binary images. The algorithms are constructed using logic opera...