Master index | Index for Mateda2.0/ScriptsMateda/OptimizationScripts

# Index for Mateda2.0/ScriptsMateda/OptimizationScripts

## Matlab files in this directory:

AffEDA_Deceptive3 | EXAMPLE 4: Aff_EDA with proportional selection and elitism 1
BayesianTree_IsingModel | EXAMPLE 10:
DefaultEDA_NKRandom | EXAMPLE 9: Bayesian tree for a multiobjective function of the NK random
DefaultEDA_OneMax | EXAMPLE 1: One Max Funtion. Default parameters
DefaultEDA_TrapFunction | EXAMPLE 11:
EBNA_Deceptive3 | EXAMPLE 2: Goldberg's deceptive function; BN K2 algorithm with BIC metric
EBNA_MultiObj_SAT | % EXAMPLE 2: MULTIO-OBJECTIVE MAXSAT
EBNA_PLS_MPC_NKRandom | EXAMPLE 16:
GaussianMultivariate_OfflineHPProtein | EXAMPLE 12: Multivariate Gaussian EDA for the Offline HP Model continuous function
GaussianNetwork_OfflineHPProtein | EXAMPLE 8: Gaussian network for the Offline HP Model continuous function
GaussianUMDA_ContSumFunction | EXAMPLE 5: Gaussian UMDA for the continuous sum function in the interval [0,5]
GaussianUMDA_OfflineHPProtein | EXAMPLE 7: Gaussian UMDA for the Offline HP Model continuous function
MOA_Deceptive3 | EXAMPLE 3: MOA algorithm with exponential selection for Goldberg's deceptive function
MixtureGaussianEDAs_OfflineHP | EXAMPLE 14: Mixtures of full Gaussian distributions
MixtureGaussianEDAs_trajectory | EXAMPLE 15: Continuous EDAs that learn mixtures of distributions
MkFDA_HPProtein | EXAMPLE 6: Markov Chain FDA for the HP protein model.
TreeFDA_Deceptive3 | EXAMPLE 17: Goldberg's deceptive function; Tree EDA algorithm
TreeFDA_HPProtein | EXAMPLE 18: Tree-FDA for the HP protein model (The tree structure is
UMDA_OneMax | Creating UMDA for OneMax.
VariantsGaussianEDAs_trajectory | EXAMPLE 13: Different variants of continuous EDAs for a spacecraft