genetiK::gp::st::Individual Class Reference
[Strongly Typed Genetic Programming framework]

Individual: GP-ST-specific Individual. More...

#include <Individual.h>

Inheritance diagram for genetiK::gp::st::Individual:

[legend]Collaboration diagram for genetiK::gp::st::Individual:

[legend]List of all members.

Public Member Functions
	Individual (IndividualFactory *individualFactory)
	creates an Individual and generates its tree.
	Individual (const Individual &individual)
	creates a copy of an Individual
virtual	~Individual (void)
	destructor
virtual double	fitness ()=0
	The fitness function.
virtual genetiK::Individual *	copy () const =0
	Copy this individual.
virtual int	mutate (const double mutationProbabilty)
	mutate the individual
virtual int	crossOver (genetiK::Individual *i, genetiK::Individual **child1, genetiK::Individual **child2)
	Cross over.
virtual list< Gene * >	extractListByType (GeneType geneType)
	Extract a typed list from the tree.

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Detailed Description

Individual: GP-ST-specific Individual.

This class extends the generic genetiK::Individual. It represents an individual as a gene tree, with the type constraints.

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Constructor & Destructor Documentation

genetiK::gp::st::Individual::Individual (  IndividualFactory *  individualFactory  )

creates an Individual and generates its tree. Parameters: individualFactory  specifies the individualFactory used to generate the tree See also: Individual(const Individual& individual)

genetiK::gp::st::Individual::Individual (  const Individual &  individual  )

creates a copy of an Individual Parameters: individual  the Individual to be copied See also: Individual(const Individual& individual)

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Member Function Documentation

virtual genetiK::Individual* genetiK::gp::st::Individual::copy (   )  const [pure virtual]

Copy this individual. copy this Individual. You should override this function in your Individual implementation, and return the appropriate new Individual, possibly, using the copy constructor. See also: Individual(const Individual& individual) Implements genetiK::gp::Individual.

int genetiK::gp::st::Individual::crossOver (  genetiK::Individual *  i, genetiK::Individual **  child1, genetiK::Individual **  child2 )  [virtual]

Cross over. This is the same as gp::Individual::crossOver with the type constraint. Parameters: i  the partner of the cross over. child1  the first child. child2  the second child. See also: gp::Individual::crossOver(genetiK::Individual* i,genetiK::Individual** child1,genetiK::Individual** child2) Reimplemented from genetiK::gp::Individual.

list< Gene * > genetiK::gp::st::Individual::extractListByType (  GeneType  geneType  )  [virtual]

Extract a typed list from the tree. This method is used by the cross over, to excract a list of gene by type. Parameters: geneType  the type

virtual double genetiK::gp::st::Individual::fitness (   )  [pure virtual]

The fitness function. a function that quantifies the optimality of a solution. You should override this function in your Individual implementation, and evaluate your own fitness. Implements genetiK::gp::Individual.

int genetiK::gp::st::Individual::mutate (  const double  mutationProbabilty  )  [virtual]

mutate the individual This function is very similar to the gp::Individual::mutate, it only adds the type constraints. Parameters: mutationProbabilty  the probability of the mutation, GP mutate each Individual with this probability. Note that GA mutate each bit with this probability. This function is very similar to the gp::Individual::mutate, it only adds the type constraints. See also: gp::Individual::mutate(const double mutationProbabilty) Reimplemented from genetiK::gp::Individual.

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The documentation for this class was generated from the following files:

• devel/genetik/src/gp/st/Individual.h
• devel/genetik/src/gp/st/Individual.cpp

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