Paper Info
Title
Trading accuracy for simplicity in evolutionary algorithms
Abstract
Many evolutionary algorithms efficient to solve a wide range of problems have been proposed and validated in the literature. We call the problem addressed in this paper “the problem of refining the design”. Given an evolutionary algorithm that includes many operators, we would like to assess if all of the latter are really relevant to accomplish the former's performance. In this paper, we present a framework to evaluate an evolutionary algorithm that has already been designed. The goal of this evaluation is to study the choices that we have to simplify the code in respect to its results accuracy. The results show that an efficient tuner can assist us in this task by obtaining information that help design decisions.
Year
DOI
Venue
2013
10.1109/CEC.2013.6557951
IEEE Congress on Evolutionary Computation
Keywords
Field
DocType
evolutionary computation,design refining,evolutionary algorithm,trading accuracy
Memetic algorithm,Interactive evolutionary computation,Mathematical optimization,Evolutionary algorithm,Human-based evolutionary computation,Computer science,Evolutionary computation,Artificial intelligence,Cultural algorithm,Evolutionary programming,Evolutionary music,Machine learning
Conference
ISBN
Citations 
PageRank 
978-1-4799-0452-5
0
0.34
References 
Authors
8
2
Name
Order
Citations
PageRank
María Cristina Riff131.75
Elizabeth Montero26910.14