Created by W.Langdon from gp-bibliography.bib Revision:1.7954
We use reflection in the domain of grammatical evolution (GE) to achieve a novel means of robustness by autonomously repairing damaged programs, improving continuity in the search and allowing programs to be evolved effectively using soft grammars. In most implementations of GE, individuals whose programs encounter errors are assigned the worst possible fitness; using the techniques described here, these individuals may be allowed to continue evolving.
We describe two different approaches to achieving robustness through reflection, and evaluate their effectiveness through a series of experiments carried out on benchmark regression problems. Results demonstrate a statistically significant improvement on the fitness of the best individual found during evolution.",
Also known as \cite{SS-ALife14b}
broken Nov 2020 http://mitpress.mit.edu/books/artificial-life-14 ALIFE14NYC@gmail.com",
Genetic Programming entries for Christopher Timperley Susan Stepney