The theory of evolution strategies
The theory of evolution strategies
Numerical Optimization of Computer Models
Numerical Optimization of Computer Models
On The Convergence Properties Of A Simple Self-adaptive Evolutionary Algorithm
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Convergence Velocity Of Evolutionary Algorithm With Self-adaptation
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Analyzing the (1, λ) evolution strategy via stochastic approximation methods
Evolutionary Computation
Parameter control in evolutionary algorithms
IEEE Transactions on Evolutionary Computation
Reconsidering the progress rate theory for evolution strategies in finite dimensions
Proceedings of the 8th annual conference on Genetic and evolutionary computation
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Based on the theory of non-negative super martingales, convergence results are proven for adaptive (1, λ) - ES (i.e. with Gaussian mutations), and geometrical convergence rates are derived. In the d-dimensional case (d 1), the algorithm studied here uses a different step-size update in each direction. However, the critical value for the step-size, and the resulting convergence rate do not depend on the dimension. Those results are discussed with respect to previous works. Rigorous numerical investigations on some 1-dimensional functions validate the theoretical results. Trends for future research are indicated.