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.
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Craven, M.J., Jimbo, H.C. (2011). A Kolmogorov-Type Stability Measure for Evolutionary Algorithms. In: Merz, P., Hao, JK. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2011. Lecture Notes in Computer Science, vol 6622. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20364-0_3
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DOI: https://doi.org/10.1007/978-3-642-20364-0_3
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