makeAgeFitnessComplexityParetoGpSearchHeuristic: Age Fitness Complexity Pareto GP Search Heuristic for RGP
In rgp: R genetic programming framework

The search-heuristic, i.e. the concrete GP search algorithm, is a modular component of RGP. makeAgeFitnessComplexityParetoGpSearchHeuristic creates a RGP search-heuristic that implements a generational evolutionary multi objective optimization algorithm (EMOA) that selects on three criteria: Individual age, individual fitness, and individual complexity.

makeAgeFitnessComplexityParetoGpSearchHeuristic(lambda = 50,
  crossoverProbability = 0.5, enableComplexityCriterion = TRUE,
  enableAgeCriterion = FALSE, ndsParentSelectionProbability = 0,
  ndsSelectionFunction = nds_cd_selection, complexityMeasure = function(ind,
  fitness) fastFuncVisitationLength(ind), ageMergeFunction = max,
  newIndividualsPerGeneration = if (enableAgeCriterion) 50 else 0,
  newIndividualsMaxDepth = 8, newIndividualFactory = makePopulation)

`lambda`	The number of children to create in each generation (`50` by default).
`crossoverProbability`	The crossover probability for search-heuristics that support this setting (i.e. TinyGP). Defaults to `0.5`.
`enableComplexityCriterion`	Whether to enable the complexity criterion in multi-criterial search heuristics.
`enableAgeCriterion`	Whether to enable the age criterion in multi-criterial search heuristics.
`ndsParentSelectionProbability`	The probability to use non-dominated sorting to select parents for each generation. When set to `0.0`, parents are selected by uniform random sampling without replacement every time. Defaults to `1.0`.
`ndsSelectionFunction`	The function to use for non-dominated sorting in Pareto GP selection. Defaults to `nds_cd_selection`.
`complexityMeasure`	The complexity measure, a function of signature `function(ind, fitness)` returning a single numeric value.
`ageMergeFunction`	The function used for merging ages of crossover children, defaults to `max`.
`newIndividualsPerGeneration`	The number of new individuals per generation to insert into the population. Defaults to `50` if `enableAgeCriterion == TRUE` else to `0`.
`newIndividualsMaxDepth`	The maximum depth of new individuals inserted into the population.
`newIndividualFactory`	The factory function for creating new individuals. Defaults to `makePopulation`.