|
gptkbp:instanceOf
|
mathematical optimization
|
|
gptkbp:approach
|
stochastic
black-box optimization
population-based
|
|
gptkbp:compatibleWith
|
crossover (in original form)
|
|
gptkbp:distinctFrom
|
genetic algorithms (focus on mutation, not crossover)
|
|
gptkbp:field
|
gptkb:artificial_intelligence
gptkb:machine_learning
gptkb:evolutionary_computation
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
evolution strategies
|
|
gptkbp:influenced
|
modern evolutionary computation
|
|
gptkbp:introduced
|
gptkb:Ingo_Rechenberg
gptkb:Hans-Paul_Schwefel
|
|
gptkbp:introducedIn
|
1960s
|
|
gptkbp:mainActivity
|
optimization of real-valued parameters
|
|
gptkbp:notableFor
|
aerodynamic design
engineering optimization
machine learning hyperparameter tuning
|
|
gptkbp:notablePublication
|
gptkb:Ingo_Rechenberg's_PhD_thesis_(1971)
|
|
gptkbp:objective
|
find optimal solutions in complex search spaces
|
|
gptkbp:originatedIn
|
gptkb:Germany
|
|
gptkbp:relatedTo
|
gptkb:genetic_algorithms
evolutionary algorithms
|
|
gptkbp:usedIn
|
continuous optimization
high-dimensional optimization
noisy optimization problems
|
|
gptkbp:uses
|
mutant
recombination
selection
|
|
gptkbp:variant
|
gptkb:(μ+λ)-ES
gptkb:(μ/ρ,λ)-ES
(1+1)-ES
|
|
gptkbp:bfsParent
|
gptkb:Hans-Paul_Schwefel
gptkb:Evolutionary_Computation
gptkb:Daan_Wierstra
|
|
gptkbp:bfsLayer
|
7
|