RT Journal Article
T1 Math Oracles: A New Way of Designing Efficient Self-Adaptive Algorithms
A1 Luque-Polo, Gabriel Jesús
A1 Alba-Torres, Enrique
K1 Lenguajes de programación
K1 Computación evolutiva
K1 Algoritmos genéticos
AB In this paper we present a new general  methodology to develop self-adaptive methods at a low computational cost. Instead of going purely ad-hoc we de ne several simple steps to include theoretical models as additional information in our algorithm. Our idea is to incorporate the predictive information (future behavior) provided by well-known mathematical models or other prediction systems (the oracle) to build enhanced methods. We show the main steps which should be considered to include this new kind of information into any algorithm. In addition, we actually test the idea on a speci c algorithm, a genetic algorithm (GA). Experiments show that our proposal is able to obtain similar, or even better results when it is compared to the  traditional algorithm. We also show the bene ts in terms of saving time and a lower complexity of parameter settings.
PB ACM Press
YR 2013
FD 2013
LK http://hdl.handle.net/10630/5612
UL http://hdl.handle.net/10630/5612
LA eng
NO G. Luque, E. Alba, Math Oracles: A New Way of Designing Efficient Self-Adaptive Algorithms, Proceedings of the Genetic and Evolutionary Computation Conference Companion,pp. 217-218, GECCO'13, July 6–10, 2013, Amsterdam, The Netherlands. ACM 2013, ISBN 978-1-4503-1964-5.
NO Universidad de Málaga. Proyecto roadME (TIN2011-28194)
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 24 ene 2026