Abstract. Turing machines are playing an increasingly significant role in Computer Science domains such as bioinformatics. Instead of directly formulating a solution to a problem, ...
Two prominent genetic programming approaches are the graph-based Cartesian Genetic Programming (CGP) and Linear Genetic Programming (LGP). Recently, a formal algorithm for construc...
We present N-gram GP, an estimation of distribution algorithm for the evolution of linear computer programs. The algorithm learns and samples the joint probability distribution of...
Abstract. This work postulates a mechanism by which random genotypic variation is directed towards favourable phenotypic variation. Evolvability is a poorly understood concept at p...
We present PlasmidPL, a plasmid-inspired programming language designed for Genetic Programming (GP), and based on a chemical metaphor. The basic data structures in PlasmidPL are ci...
We present an approach for the automated synthesis of proactive aggregation protocols using Genetic Programming and discuss major decisions in modeling and simulating distributed a...
Many automatically-synthesized programs have, like their hand-made counterparts, numerical parameters that need to be set properly before they can show an acceptable performance. H...