Implement "Learning ALPS"

[pfleck]

Since ALPS is capable of regularly produce new random populations in the bottom layer, we could take information from higher layers and steer the random creation in promising directions.

For instance, in GP, we could vary the symbol and variable frequencies for the random population by analyzing which symbols and variables perform well in the upper layers. Additionally, we could also increase diversity by specifically generate individuals in the search area where the top layers haven't been looking.

[pfleck]

r17852 Created branch.

[pfleck]

r17854 Added a new operator hook for ALPS for adapting the reinitialization strategy.

[bburlacu]

r17857: Implement crude initial reinitialization concept.

[pfleck]

r17916 Added missing placeholder for the Reinitialization Strategy.

[pfleck]

r17947 Added MinimumFrequency and LearningRate parameters to symbol frequency and node impact strategy controllers.