We show how the understandability and speed of genetic programming classification algorithms can be improved, without affecting the classification accuracy. By analyzing the dec...
Abstract. This paper describes a new approach for parameter optimization that uses a novel representation for the parameters to be optimized. By using genetic programming, the new ...
This article introduces a tool for data fitting that is based on genetic programming and especially on the grammatical evolution technique. The user needs to input a series of poi...
Ioannis G. Tsoulos, Dimitris Gavrilis, Evangelos D...
Abstract. This paper describes a parallel model for a distributed memory architecture of a non traditional evolutionary computation method, which integrates constraint propagation ...
We present the Genetic L-System Programming (GLP) paradigm for evolutionary creation and development of parallel rewrite systems (Lsystems, Lindenmayer-systems) which provide a com...