Ensemble Phased Genetic Programming for Roundabout Turn Restriction Prediction
Created by W.Langdon from
gp-bibliography.bib Revision:1.8469
- @InProceedings{chitty:2025:GECCO,
-
author = "Darren Chitty and Ayah Helal and Sareh Rowlands and
Craig Willis and Christopher Underwood and
Ed Keedwell",
-
title = "Ensemble Phased Genetic Programming for Roundabout
Turn Restriction Prediction",
-
booktitle = "Proceedings of the 2025 Genetic and Evolutionary
Computation Conference",
-
year = "2025",
-
editor = "Roman Kalkreuth and Alexander Brownlee",
-
pages = "1345--1353",
-
address = "Malaga, Spain",
-
series = "GECCO '25",
-
month = "14-18 " # jul,
-
organisation = "SIGEVO",
-
publisher = "Association for Computing Machinery",
-
publisher_address = "New York, NY, USA",
-
keywords = "genetic algorithms, genetic programming, Real World
Applications, GIS",
-
isbn13 = "979-8-4007-1465-8",
-
URL = "
https://doi.org/10.1145/3712256.3726424",
-
DOI = "
doi:10.1145/3712256.3726424",
-
size = "9 pages",
-
abstract = "Ensemble methods are among the best performing in the
machine learning literature, often outperforming single
methods in training accuracy and the prevention of
overfitting. This work builds on the previously
successful phased genetic programming (GP) approach to
build ensembles of GP trees to create ensemble phased
GP (EPGP). The method is tested in a real-world
transportation modelling problem, the roundabout
(traffic circle, rotary) turn restriction problem using
data from OpenStreetMap, an important and
time-consuming element of the traffic modelling
process. EPGP is compared with standard and phased GP
formulations and representative algorithms from the
machine learning literature and is found to outperform
them on this task.",
-
notes = "GECCO-2025 RWA A Recombination of the 34th
International Conference on Genetic Algorithms (ICGA)
and the 30th Annual Genetic Programming Conference
(GP)",
- }
Genetic Programming entries for
Darren M Chitty
Ayah Helal
Sareh Rowlands
Craig Willis
Christopher Underwood
Ed Keedwell
Citations