Paper Info
Title
Tailoring Mutation to Landscape Properties
Abstract
We present numerical results on Kauffman's NK landscape family indicating that the optimal distance at which to search for fitter variants depends on both the current fitness and the sampling that can be afforded at each distance. The optimal search distance from average fitness configurations is large to escape local correlation limits and decreases as fitness increases. An analytic derivation of the optimal search distance as a function the landscape correlation \rho, the current fitness f_|ì, ...
Year
DOI
Venue
1998
10.1007/BFb0040788
Evolutionary Programming
Keywords
Field
DocType
landscape properties,tailoring mutation
Search algorithm,Fitness landscape,Evolutionary algorithm,Algorithm complexity,Algorithm,Correlation,Sampling (statistics),Genetic algorithm,Mathematics
Conference
ISBN
Citations 
PageRank 
3-540-64891-7
1
0.36
References 
Authors
5
1
Name
Order
Citations
PageRank
William G. Macready116139.07