Abstract
When considering continuous spaces EA, a convenient tool to model these algorithms is perturbation theory. In this paper we present preliminary results, derived from Freidlin-Wentzell theory, related to the convergence of a simple EA model. The main result of this paper yields a bound on sojourn times of the Markov process in subsets centered around the maxima of the fitness function. Exploitation of this result opens the way to convergence speed bounds with respect to some statistical measures on the fitness function (likely related to irregularity).
Keywords
- Genetic Algorithm
- Evolutionary Algorithm
- Sojourn Time
- Markov Chain Monte Carlo Method
- Exponential Moment
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Landrin-Schweitzer, Y., Lutton, E. (2000). Perturbation Theory for Evolutionary Algorithms: Towards an Estimation of Convergence Speed. In: Schoenauer, M., et al. Parallel Problem Solving from Nature PPSN VI. PPSN 2000. Lecture Notes in Computer Science, vol 1917. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45356-3_11
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DOI: https://doi.org/10.1007/3-540-45356-3_11
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