Efficient linkage discovery by limited probing

Authors:
Robert B. Heckendorn;Alden H. Wright
Affiliations:
University of Idaho, Moscow, ID;Computer Science, University of Montana, Missoula, MT
Venue:
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Year:
2003

Citing 6
Cited 9

Schemata, Distributions and Graphical Models in Evolutionary Optimization

Journal of Heuristics
Embedded landscapes

Evolutionary Computation
Walsh analysis, epistasis, and optimization problem difficulty for evolutionary algorithms

Walsh analysis, epistasis, and optimization problem difficulty for evolutionary algorithms
Gene Expression and Fast Construction of Distributed Evolutionary Representation

Evolutionary Computation
Predicting epistasis from mathematical models

Evolutionary Computation
Linkage identification by non-monotonicity detection for overlapping functions

Evolutionary Computation

On the convergence of an estimation of distribution algorithm based on linkage discovery and factorization

GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Space Complexity of Estimation of Distribution Algorithms

Evolutionary Computation
A crossover for complex building blocks overlapping

Proceedings of the 8th annual conference on Genetic and evolutionary computation
Linkage identification by fitness difference clustering

Evolutionary Computation
Optimal query complexity bounds for finding graphs

STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
Empirical investigations on parallel competent genetic algorithms

Proceedings of the 10th annual conference on Genetic and evolutionary computation
Lower and upper bounds for linkage discovery

IEEE Transactions on Evolutionary Computation
Sub-structural niching in non-stationary environments

AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
Population sizing of dependency detection by fitness difference classification

FOGA'05 Proceedings of the 8th international conference on Foundations of Genetic Algorithms

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper addresses the problem of determining the epistatic linkage of a function from binary strings to the reals. There is a close relationship between the Walsh coefficients of the function and "probes" (or perturbations) of the function. This relationship leads to two linkage detection algorithms that generalize earlier algorithms of the same type. A rigorous complexity analysis is given of the first algorithm. The second algorithm not only detects the epistatic linkage, but also computes all of theWalsh coefficients. This algorithm is much more efficient than previous algorithms for the same purpose.