– This article presents a new approach to the evolution of controllers for autonomous agents. We propose the evolution of a connectionist structure where each node has an associa...
Genetic programming is known to be capable of creating designs that satisfy prespecified high-level design requirements for analog electrical circuits and other complex structures...
John R. Koza, Forrest H. Bennett III, Oscar Stiffe...
We have explored a novel method to find textual relations in electronic documents using genetic programming and semantic networks. This can be used for enhancing information retri...
Genetic programming tackles the issue of how to automatically create a working computer program for a given problem from some initial problem statement. The goal is accomplished i...
Abstract. In this paper we continue our study on adaptive genetic programming. We use Stepwise Adaptation of Weights (saw) to boost performance of a genetic programming algorithm o...
Self-Modifying Cartesian Genetic Programming (SMCGP) is a form of genetic programming that integrates developmental (self-modifying) features as a genotype-phenotype mapping. This...
Simon Harding, Julian Francis Miller, Wolfgang Ban...
Nowadays, object recognition is widely studied under the paradigm of matching local features. This work describes a genetic programming methodology that synthesizes mathematical e...
A new model of Genetic Programming with variable size population is presented in this paper and applied to the reconstruction of target functions in dynamic environments (i.e. pro...
In this paper, we present a detailed analysis of the application of Genetic Programming to the evolution of distributed algorithms. This research field has many facets which make...
Many evolutionary computation search spaces require fitness assessment through the sampling of and generalization over a large set of possible cases as input. Such spaces seem par...