Paper Info
Title
On the mutual information as a fitness landscape measure.
Abstract
Fitness landscape analysis plays an important role in both theoretical and practical perspectives when using evolutionary algorithms. In this paper, we develop a new measure based on the mutual information paradigm and we show how it can help to deduce further information about the fitness landscape. In order to validate it as a valuable source of information when conducting fitness landscape analysis, we investigate its properties on a well-known benchmark suite. Moreover, we investigate the usefulness of the obtained information when choosing crossover operators. Finally, we show that when using our new measure, a number of classifiers can be constructed that offer an improved accuracy.
Year
DOI
Venue
2017
10.1145/3067695.3076082
GECCO (Companion)
Keywords
Field
DocType
Fitness landscape, Single-objective, Mutual Information, Performance comparison
Crossover,Fitness landscape,Evolutionary algorithm,Suite,Computer science,Fitness function,Operator (computer programming),Mutual information,Artificial intelligence,Single objective,Machine learning
Conference
Citations 
PageRank 
References 
0
0.34
2
Authors
4
Name
Order
Citations
PageRank
Rebeka Coric121.75
Stjepan Picek216444.70
Domagoj Jakobovic319529.01
C. A. Coello Coello45799427.99