A scalable symbolic expression tree interpreter for the heuristiclab optimization framework

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@InProceedings{Cirillo:2014:GECCOcomp,

• author = "Simone Cirillo and Stefan Lloyd",
• title = "A scalable symbolic expression tree interpreter for the heuristiclab optimization framework",
• booktitle = "GECCO 2014 Workshop on Evolutionary Computation Software Systems (EvoSoft)",
• year = "2014",
• editor = "Stefan Wagner and Michael Affenzeller",
• isbn13 = "978-1-4503-2881-4",
• keywords = "genetic algorithms, genetic programming",
• pages = "1141--1148",
• month = "12-16 " # jul,
• organisation = "SIGEVO",
• address = "Vancouver, BC, Canada",
• URL = "http://doi.acm.org/10.1145/2598394.2605692",
• DOI = "doi:10.1145/2598394.2605692",
• publisher = "ACM",
• publisher_address = "New York, NY, USA",
• abstract = "In this paper we describe a novel implementation of the Interpreter class for the metaheuristic optimisation framework HeuristicLab, comparing it with the three existing interpreters provided with the framework. The Interpreter class is an internal software component used by HeuristicLab for the evaluation of the symbolic expression trees on which its Genetic Programming (GP) implementation relies. The proposed implementation is based on the creation and compilation of a .NET Expression Tree. We also analyse the Interpreters' performance, evaluating the algorithm execution times on GP Symbolic Regression problems for different run settings. Our implementation results to be the fastest on all evaluations, with comparatively better performance the larger the run population size, dataset length and tree size are, increasing HeuristicLab's computational efficiency for large problem setups.",
• notes = "Also known as \cite{2605692} Distributed at GECCO-2014.",

}

Genetic Programming entries for Simone Cirillo Stefan Lloyd

Citations