xegaGpInitGeneGe {xegaGpGene}R Documentation

Generates a gene as a random derivation tree from a random integer vector.

Description

For a given grammar, xegaGpInitGene() generates a gene as a random derivation tree with a depth-bound. This function uses almost the same initialization algorithm as for grammatical evolution.

Usage

xegaGpInitGeneGe(lF)

Arguments

lF

Local configuration of the genetic algorithm.

Details

In the derivation tree representation of package xegaGpGene, a gene is a list with

  1. $gene1: a derivation tree.

  2. $fit: The fitness of the genotype of $gene1

  3. $evaluated: Boolean: TRUE if the fitness is known.

  4. $evalFail: Has the evaluation of the gene failed?

  5. $var: The cumulative variance of the fitness of all evaluations of a gene. (For stochastic functions)

  6. $sigma: The standard deviation of the fitness of all evaluations of a gene. (For stochastic functions)

  7. $obs: The number of evaluations of a gene. (For stochastic functions)

The algorithm for generating a complete derivation tree with a depth-bound is imported from the package xegaDerivationTrees.

Value

Derivation tree.

See Also

Other Gene Generation: xegaGpInitGene()

Examples

gene<-xegaGpInitGeneGe(lFxegaGpGene)
xegaGpDecodeGene(gene, lFxegaGpGene)


[Package xegaGpGene version 1.0.0.2 Index]