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Title: CMA-ES Download
 Description: The optimization behavior of the self-adaptation (SA) evolution strategy (ES) with intermediate multirecombination (the (=I )-SA-ES) using isotropic mutations is investigated on the general elliptic objective function. An asymptotically exact quadratic progress rate formula is derived. This is used to model the dynamical ES system by a set of difference equations. The solutions of this system are used to analytically calculate the optimal learning parameter  . The theoretical results are compared and validated by comparison with real (=I )-SA-ES runs on typical elliptic test model cases. The theoretical results clearly indicate that using a model-independent learning parameter  leads to suboptimal performance of the (=I )-SA-ES on objective functions with changing local condition numbers as often encountered in practical problems with complex fitness landscapes.
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CMA-ES
......\Ackley.m
......\CMAES.asv
......\CMAES.m
......\CMAES1.asv
......\CMAES1.m
......\ClearDups.m
......\ComputeAveCost.m
......\Conclude.m
......\GA.m
......\Init.m
......\PopSort.m
......\Rosenbrock.m
......\Sphere.m
......\Step.m
......\picture for test
......\purecmaes.asv
......\purecmaes.m
......\purecmaes1.asv
......\purecmaes1.m
......\purecmaes_original.m
......\readme.txt
    

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