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java.lang.Objectorg.vizzini.ai.geneticalgorithm.AbstractGeneticAlgorithm
org.vizzini.ai.geneticprogramming.AbstractGeneticAlgorithmGP
org.vizzini.ai.geneticprogramming.example.XOR
public class XOR
Provides an example XOR problem using genetic programming.
Field Summary |
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Fields inherited from class org.vizzini.ai.geneticalgorithm.AbstractGeneticAlgorithm |
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_crossoverFraction, _crossoverType, _elapsedTime, _generation |
Constructor Summary | |
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XOR()
Construct this object. |
Method Summary | |
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protected IFitnessCase |
createFitnessCase(boolean x0,
boolean x1,
boolean y)
Create a fitness case for the given parameters. |
protected int |
evaluateFitness(int index,
IChromosomeGP chromosome,
boolean isPrinting)
Evaluate the fitness of the given chromosome for this problem. |
protected int |
getPerfectFitness()
Return the perfect fitness. |
protected Class |
getReturnType()
Return the overall return type for the chromosomes. |
static void |
main(String[] args)
Application method. |
Methods inherited from class org.vizzini.ai.geneticprogramming.AbstractGeneticAlgorithmGP |
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addFunction, addTerminal, createChromosome, evaluateFitness, getContext, getFunctionCount, getFunctionGenerator, getInitialMaxDepth, getTerminalCount, isSimpleBetter, onePointCrossover, penalizeComplexity, setContext, setInitialMaxDepth, setSimpleBetter |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Methods inherited from interface org.vizzini.ai.geneticalgorithm.IGeneticAlgorithm |
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getCrossoverFraction, getCrossoverType, getElapsedTime, getGeneration, getMostFit, getMutationFraction, getMutationMagnitude, getMutationRate, getPopulationSize, getProcessingRate, reset, runGenerations, setAverageCrossoverFraction, setCrossoverFraction, setCrossoverType, setDuplicateAllowed, setMutationFraction, setMutationMagnitude, setMutationRate, setPopulationSize, writeReport |
Constructor Detail |
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public XOR()
Method Detail |
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public static final void main(String[] args)
args
- Input arguments.protected IFitnessCase createFitnessCase(boolean x0, boolean x1, boolean y)
x0
- Input value.x1
- Input value.y
- Output value.protected int evaluateFitness(int index, IChromosomeGP chromosome, boolean isPrinting)
evaluateFitness
in class AbstractGeneticAlgorithmGP
chromosome
- Chromosome.isPrinting
- Flag indicating if the method should print.protected int getPerfectFitness()
getPerfectFitness
in class AbstractGeneticAlgorithm
protected Class getReturnType()
getReturnType
in class AbstractGeneticAlgorithmGP
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Copyright © 2007 Vizzini.org. All Rights Reserved. | 2007.12.25.03.00.02 |