A connectionist machine for genetic hillclimbing
A connectionist machine for genetic hillclimbing
Global optimization
Kalman filtering: theory and practice
Kalman filtering: theory and practice
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
Evolution strategies –A comprehensive introduction
Natural Computing: an international journal
Proceedings of the 6th International Conference on Genetic Algorithms
Learning probability distributions in continuous evolutionary algorithms– a comparative review
Natural Computing: an international journal
Completely Derandomized Self-Adaptation in Evolution Strategies
Evolutionary Computation
An analysis of mutative σ-self-adaptation on linear fitness functions
Evolutionary Computation
Performance analysis of niching algorithms based on derandomized-ES variants
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Niching with derandomized evolution strategies in artificial and real-world landscapes
Natural Computing: an international journal
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
pCMALib: a parallel fortran 90 library for the evolution strategy with covariance matrix adaptation
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Benchmarking the (1+1)-CMA-ES on the BBOB-2009 function testbed
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Adaptive niche radii and niche shapes approaches for niching with the cma-es
Evolutionary Computation
Steady-state selection and efficient covariance matrix update in the multi-objective CMA-ES
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
Active covariance matrix adaptation for the (1+1)-CMA-ES
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Improved step size adaptation for the MO-CMA-ES
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Benchmarking a weighted negative covariance matrix update on the BBOB-2010 noiseless testbed
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Benchmarking a weighted negative covariance matrix update on the BBOB-2010 noisy testbed
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Mirrored sampling and sequential selection for evolution strategies
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
Multimodal optimization by means of a topological species conservation algorithm
IEEE Transactions on Evolutionary Computation
Not all parents are equal for MO-CMA-ES
EMO'11 Proceedings of the 6th international conference on Evolutionary multi-criterion optimization
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Information Sciences: an International Journal
A Differential Covariance Matrix Adaptation Evolutionary Algorithm for real parameter optimization
Information Sciences: an International Journal
Ockham's Razor in memetic computing: Three stage optimal memetic exploration
Information Sciences: an International Journal
Gaussian adaptation revisited: an entropic view on covariance matrix adaptation
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
International Journal of Robotics Research
A (1+1)-CMA-ES for constrained optimisation
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Quantum control experiments as a testbed for evolutionary multi-objective algorithms
Genetic Programming and Evolvable Machines
A distributed agent-based approach for simulation-based optimization
Advanced Engineering Informatics
An empirical comparison of CMA-ES in dynamic environments
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part I
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First, the covariance matrix adaptation (CMA) with rank-one update is introduced into the (1+1)-evolution strategy. An improved implementation of the 1/5-th success rule is proposed for step size adaptation, which replaces cumulative path length control. Second, an incremental Cholesky update for the covariance matrix is developed replacing the computational demanding and numerically involved decomposition of the covariance matrix. The Cholesky update can replace the decomposition only for the update without evolution path and reduces the computational effort from O(n3) to O(n2). The resulting (1+1)-Cholesky-CMA-ES is an elegant algorithm and the perhaps simplest evolution strategy with covariance matrix and step size adaptation. Simulations compare the introduced algorithms to previously published CMA versions.