com.epochx.model.multiplexer
Class Multiplexer6Bit

java.lang.Object
  com.epochx.core.GPAbstractModel<java.lang.Boolean>
      com.epochx.model.multiplexer.Multiplexer6Bit

All Implemented Interfaces:

GPModel<java.lang.Boolean>, CrossoverListener<java.lang.Boolean>, ElitismListener<java.lang.Boolean>, GenerationListener, InitialisationListener<java.lang.Boolean>, LifeCycleListener<java.lang.Boolean>, MutationListener<java.lang.Boolean>, PoolSelectionListener<java.lang.Boolean>, ReproductionListener<java.lang.Boolean>, TerminationListener, CrossoverStatListener, GenerationStatListener, MutationStatListener, RunStatListener

public class Multiplexer6Bit
extends GPAbstractModel<java.lang.Boolean>

Constructor Summary

Multiplexer6Bit()

Method Summary

void	configure()
double	getFitness(CandidateProgram<java.lang.Boolean> program) Calculates and returns the fitness score of the given program.
java.util.List<FunctionNode<java.lang.Boolean>>	getFunctions() Retrieves the set of function nodes.
java.util.List<TerminalNode<java.lang.Boolean>>	getTerminals() Retrieves the set of terminal nodes.

Methods inherited from class com.epochx.core.GPAbstractModel

acceptCrossover, acceptMutation, crossoverStats, generationStats, getCrossover, getCrossoverProbability, getCrossoverStatFields, getCrossoverStatListener, getGenerationStatListener, getGenStatFields, getInitialiser, getInitialMaxDepth, getLifeCycleListener, getMaxProgramDepth, getMutationProbability, getMutationStatFields, getMutationStatListener, getMutator, getNoElites, getNoGenerations, getNoRuns, getPoolSelector, getPoolSize, getPopulationSize, getProgramSelector, getReproductionProbability, getRNG, getRunStatFields, getRunStatListener, getSyntax, getTerminationFitness, mutationStats, onCrossover, onElitism, onFitnessTermination, onGenerationStart, onGenerationTermination, onInitialisation, onMutation, onPoolSelection, onReproduction, runStats, setCrossover, setCrossoverProbability, setCrossoverStatFields, setCrossoverStatListener, setGenerationStatListener, setGenStatFields, setInitialiser, setInitialMaxDepth, setLifeCycleListener, setMaxProgramDepth, setMutationProbability, setMutationStatFields, setMutationStatListener, setMutator, setNoElites, setNoGenerations, setNoRuns, setPoolSelector, setPoolSize, setPopulationSize, setProgramSelector, setRNG, setRunStatFields, setRunStatListener, setTerminationFitness

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

Multiplexer6Bit

public Multiplexer6Bit()

Method Detail

configure

public void configure()

getFunctions

public java.util.List<FunctionNode<java.lang.Boolean>> getFunctions()

Description copied from interface: GPModel

Retrieves the set of function nodes.

Returns:

the function nodes to be used during evolution.

getTerminals

public java.util.List<TerminalNode<java.lang.Boolean>> getTerminals()

Description copied from interface: GPModel

Retrieves the set of terminal nodes.

Returns:

the terminal nodes to be used during evolution.

getFitness

public double getFitness(CandidateProgram<java.lang.Boolean> program)

Description copied from interface: GPModel

Calculates and returns the fitness score of the given program. The score returned by this method provides the underlying way in which Candidate Programs are selected. The GP system will attempt to improve the value returned by this method over the generations. A fitness value of 0.0 is better than a fitness value of 1.0.

There are many ways in which a fitness score can be calculated, for example mean squared error, standard deviation or a simple count of how many known inputs the given program provides incorrect (known) outputs. For more information, the new user should read some of the genetic programming literature.

Parameters:

program - the CandidateProgram to evaluate and calculate a score for.

Returns:

a double representing the quality of the program where a small value is considered better than a larger value.