Model Assisted Evolution Strategy - MAES
In the pre-selection concept lambdaPlus>lambda
individuals are generated from mu parents.
All lambdaPlus individuals are evaluated by a
surrogate model of the fitness landscape and the estimated
fitness values are used to pre-select the lambda
best individuals, which will be evaluated with
the real fitness function.
The model is trained at the beginning with a randomly created
initial population and is updated after each generation
step with lambda new fitness cases.
The idea behind this approach is that only the
most promising individuals with a good fitness prediction
are evaluated with the true fitness function.
Every generation a new offspring lambda is evaluated with the real fitness function,
the model is updated with this information of \lambda fitness cases.