Effective simplification of evolved push programs using a simple, stochastic hill-climber

Created by W.Langdon from gp-bibliography.bib Revision:1.8010

@InProceedings{Spector:2014:GECCOcomp,

• author = "Lee Spector and Thomas Helmuth",
• title = "Effective simplification of evolved push programs using a simple, stochastic hill-climber",
• booktitle = "GECCO Comp '14: Proceedings of the 2014 conference companion on Genetic and evolutionary computation companion",
• year = "2014",
• editor = "Christian Igel and Dirk V. Arnold and Christian Gagne and Elena Popovici and Anne Auger and Jaume Bacardit and Dimo Brockhoff and Stefano Cagnoni and Kalyanmoy Deb and Benjamin Doerr and James Foster and Tobias Glasmachers and Emma Hart and Malcolm I. Heywood and Hitoshi Iba and Christian Jacob and Thomas Jansen and Yaochu Jin and Marouane Kessentini and Joshua D. Knowles and William B. Langdon and Pedro Larranaga and Sean Luke and Gabriel Luque and John A. W. McCall and Marco A. {Montes de Oca} and Alison Motsinger-Reif and Yew Soon Ong and Michael Palmer and Konstantinos E. Parsopoulos and Guenther Raidl and Sebastian Risi and Guenther Ruhe and Tom Schaul and Thomas Schmickl and Bernhard Sendhoff and Kenneth O. Stanley and Thomas Stuetzle and Dirk Thierens and Julian Togelius and Carsten Witt and Christine Zarges",
• isbn13 = "978-1-4503-2881-4",
• keywords = "genetic algorithms, genetic programming: Poster",
• pages = "147--148",
• month = "12-16 " # jul,
• organisation = "SIGEVO",
• address = "Vancouver, BC, Canada",
• URL = "http://doi.acm.org/10.1145/2598394.2598414",
• DOI = "doi:10.1145/2598394.2598414",
• publisher = "ACM",
• publisher_address = "New York, NY, USA",
• abstract = "Genetic programming systems often produce programs that include unnecessary code. This is undesirable for several reasons, including the burdens that overly-large programs put on end-users for program interpretation and maintenance. The problem is exacerbated by recently developed techniques, such as genetic programming with geometric semantic crossover, that tend to produce enormous programs. Methods for automatically simplifying evolved programs are therefore of interest, but automatic simplification is non-trivial in the context of traditional program representations with unconstrained function sets. Here we show how evolved programs expressed in the stack-based Push programming language can be automatically and reliably simplified using a simple, stochastic hill-climber. We demonstrate and quantitatively characterise this simplification process on programs evolved to solve four non-trivial genetic programming problems with qualitatively different function sets.",
• notes = "Also known as \cite{2598414} Distributed at GECCO-2014.",

}

Genetic Programming entries for Lee Spector Thomas Helmuth

Citations