Parsimony pressure, the explicit penalization of larger programs, has been increasingly used as a means of controlling code growth in genetic programming. However, in many cases p...
In this paper we first review the main results obtained in the theory of schemata in Genetic Programming (GP) emphasising their strengths and weaknesses. Then we propose a new, s...
Process algebra are formal languages used for the rigorous specification and analysis of concurrent systems. By using a process algebra as the target language of a genetic program...
A representation-less model for genetic programming is presented. The model is intended to examine the mechanisms that lead to bloat in genetic programming (GP). We discuss two hyp...
s In data mining, we emphasize the need for learning from huge, incomplete and imperfect data sets (Fayyad et al. 1996, Frawley et al. 1991, Piatetsky-Shapiro and Frawley, 1991). T...
ct. A Bayesian framework for genetic programming GP is presented. This is motivated by the observation that genetic programming iteratively searches populations of fitter programs ...
Genetic programming is an automatic method for creating a computer program or other complex structure to solve a problem. This paper first reviews various instances where genetic p...
John R. Koza, Martin A. Keane, Jessen Yu, Forrest ...
Genetic programming, in conjunction with advanced analytical instruments, is a novel tool for the investigation of complex biological systems at the whole-tissue level. In this stu...
Helen E. Johnson, Richard J. Gilbert, Michael K. W...
The use of genetic programming for probabilistic pattern matching is investigated. A stochastic regular expression language is used. The language features a statistically sound sem...
The automatic synthesis of procedural textures for 3D surfaces using genetic programming is investigated. Genetic algorithms employ a search strategy inspired by Darwinian natural...