A comparative study of Pseudo and Quasi random sequences for the solution intergral equations
Journal of Computational Physics
Random number generation and quasi-Monte Carlo methods
Random number generation and quasi-Monte Carlo methods
Algorithm 659: Implementing Sobol's quasirandom sequence generator
ACM Transactions on Mathematical Software (TOMS)
A generalized discrepancy and quadrature error bound
Mathematics of Computation
When are quasi-Monte Carlo algorithms efficient for high dimensional integrals?
Journal of Complexity
The theory of evolution strategies
The theory of evolution strategies
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
CUTEr and SifDec: A constrained and unconstrained testing environment, revisited
ACM Transactions on Mathematical Software (TOMS)
Local and global order 3/2 convergence of a surrogate evolutionary algorithm
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Genetic algorithms using low-discrepancy sequences
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Completely Derandomized Self-Adaptation in Evolution Strategies
Evolutionary Computation
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Algorithms (x, sigma, eta): quasi-random mutations for evolution strategies
EA'05 Proceedings of the 7th international conference on Artificial Evolution
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Why one must use reweighting in estimation of distribution algorithms
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Analyzing the impact of mirrored sampling and sequential selection in elitist evolution strategies
Proceedings of the 11th workshop proceedings on Foundations of genetic algorithms
Simple tools for multimodal optimization
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
A rigorous runtime analysis for quasi-random restarts and decreasing stepsize
EA'11 Proceedings of the 10th international conference on Artificial Evolution
| Hi-index | 0.00 |
In a preliminary part of this paper, we analyze the necessity of randomness in evolutionstrategies. We conclude to the necessity of "continuous"-randomness, but with a much more limited use of randomness than whatis commonly used in evolution strategies. We then apply these results to CMA-ES, a famous evolution strategy already based on the idea of derandomization, which uses random independent Gaussian mutations. We here replace these random independent Gaussian mutations by a quasi-randomsample. The modification is very easy to do, the modified algorithm is computationally more efficient and its convergence is faster in terms of the number of iterates for a given precision.