A kolmogorov-type stability measure for evolutionary algorithms

Authors:
Matthew J. Craven;Henri C. Jimbo
Affiliations:
School of Comp. and Eng. Systems, University of Abertay Dundee, Dundee, UK;Nara Institute of Science and Technology, Ikoma, Nara, Japan
Venue:
EvoCOP'11 Proceedings of the 11th European conference on Evolutionary computation in combinatorial optimization
Year:
2011

Citing 4
Cited 0

The word problem for free partially commutative groups

Journal of Symbolic Computation
Genetic algorithms + data structures = evolution programs (3rd ed.)

Genetic algorithms + data structures = evolution programs (3rd ed.)
Combinatorial Landscapes

SIAM Review
Genetic algorithms for word problems in partially commutative groups

EvoCOP'07 Proceedings of the 7th European conference on Evolutionary computation in combinatorial optimization

Quantified Score

Hi-index	0.00

Visualization

Abstract

In previous work, EAs were shown to efficiently solve certain equations over partially commutative groups. The EAs depend on the values of several control parameters for success. Generally these values must be tuned to the structure of the equation or problem to be solved. Supposing suitable values are found, a natural concern is stability of the EA under random perturbation of its parameters. This work considers such a model of EA stability by defining neighbourhoods over EA parameter space and examining their properties. We define stability based upon Kolmogorov distance and analyse that distance between repeated random perturbations of parameters, forming a statistical indication of EA stability under parameter perturbation. We then analyse the model for the wider class of general EAs, meaning our model may serve as a framework for parameter optimisation and stability analysis.