org.encog.ml.ea.train.basic

Class BasicEA

java.lang.Object

org.encog.ml.ea.train.basic.BasicEA

All Implemented Interfaces:

java.io.Serializable, EncogShutdownTask, EvolutionaryAlgorithm, MultiThreadable

Direct Known Subclasses:

TrainEA

public class BasicEA
extends java.lang.Object
implements EvolutionaryAlgorithm, MultiThreadable, EncogShutdownTask, java.io.Serializable

Provides a basic implementation of a multi-threaded Evolutionary Algorithm. The EA works from a score function.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
BasicEA(Population thePopulation, CalculateScore theScoreFunction) Construct an EA.

Method Summary

Modifier and Type	Method and Description
boolean	addChild(Genome genome) Add a child to the next iteration.
void	addOperation(double probability, EvolutionaryOperator opp) Add an operation.
void	addScoreAdjuster(AdjustScore scoreAdjust) Add a score adjuster.
void	calculateScore(Genome g) Calculate the score for a genome.
static void	calculateScoreAdjustment(Genome genome, java.util.List<AdjustScore> adjusters) Calculate the score adjustment, based on adjusters.
void	finishTraining() Called when training is finished.
GenomeComparator	getBestComparator() Get the comparator that is used to choose the "true best" genome.
Genome	getBestGenome()
EvolutionaryOperator	getChampMutation()
GeneticCODEC	getCODEC()
double	getEliteRate()
double	getError()
int	getIteration()
int	getMaxIndividualSize()
int	getMaxOperationErrors()
int	getMaxTries()
Genome	getOldBestGenome()
OperationList	getOperators()
Population	getPopulation()
RandomFactory	getRandomNumberFactory()
java.util.List<AdjustScore>	getScoreAdjusters()
CalculateScore	getScoreFunction()
SelectionOperator	getSelection()
GenomeComparator	getSelectionComparator() Get the comparator that is used to choose the "best" genome for selection, as opposed to the "true best".
boolean	getShouldIgnoreExceptions()
Speciation	getSpeciation()
int	getThreadCount()
boolean	isValidationMode()
void	iteration() Perform a training iteration.
void	performShutdownTask()
void	reportError(java.lang.Throwable t) Called by a thread to report an error.
void	setBestComparator(GenomeComparator theComparator) Set the comparator.
void	setChampMutation(EvolutionaryOperator champMutation)
void	setCODEC(GeneticCODEC theCodec) Set the CODEC to use.
void	setEliteRate(double eliteRate)
void	setIteration(int iteration) Set the current iteration number.
void	setMaxOperationErrors(int maxOperationErrors)
void	setMaxTries(int maxTries)
void	setPopulation(Population thePopulation) Set the population.
void	setRandomNumberFactory(RandomFactory randomNumberFactory)
void	setSelection(SelectionOperator selection) Set the selection operator.
void	setSelectionComparator(GenomeComparator theComparator) Set the comparator that is used to choose the "best" genome for selection, as opposed to the "true best".
void	setShouldIgnoreExceptions(boolean b) Determines if genetic operator exceptions should be ignored.
void	setSpeciation(Speciation speciation) Set the speciation method.
void	setThreadCount(int numThreads) Set the number of threads to use.
void	setValidationMode(boolean validationMode) Determine if the genomes should be validated.

Methods inherited from class java.lang.Object

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

Constructor Detail

BasicEA

public BasicEA(Population thePopulation,
               CalculateScore theScoreFunction)

Construct an EA.

Parameters:

thePopulation - The population.

theScoreFunction - The score function.

Method Detail

calculateScoreAdjustment

public static void calculateScoreAdjustment(Genome genome,
                                            java.util.List<AdjustScore> adjusters)

Calculate the score adjustment, based on adjusters.

Parameters:

genome - The genome to adjust.

adjusters - The score adjusters.

addChild

public boolean addChild(Genome genome)

Add a child to the next iteration.

Parameters:

genome - The child.

Returns:

True, if the child was added successfully.

addOperation

public void addOperation(double probability,
                         EvolutionaryOperator opp)

Add an operation.

Specified by:

addOperation in interface EvolutionaryAlgorithm

Parameters:

probability - The probability of using this operator.

opp - The operator to add.

addScoreAdjuster

public void addScoreAdjuster(AdjustScore scoreAdjust)

Add a score adjuster. Score adjusters are used to adjust the adjusted score of a genome. This allows bonuses and penalties to be applied for desirable or undesirable traits.

Specified by:

addScoreAdjuster in interface EvolutionaryAlgorithm

Parameters:

scoreAdjust - The score adjustor to add.

calculateScore

public void calculateScore(Genome g)

Calculate the score for a genome.

Specified by:

calculateScore in interface EvolutionaryAlgorithm

Parameters:

g - The genome to calculate the score for.

finishTraining

public void finishTraining()

Called when training is finished. This allows the EA to properly shut down.

Specified by:

finishTraining in interface EvolutionaryAlgorithm

getBestComparator

public GenomeComparator getBestComparator()

Get the comparator that is used to choose the "true best" genome. This uses the real score, and not the adjusted score.

Specified by:

getBestComparator in interface EvolutionaryAlgorithm

Returns:

The best comparator.

getBestGenome

public Genome getBestGenome()

Specified by:

getBestGenome in interface EvolutionaryAlgorithm

Returns:

the bestGenome

getChampMutation

public EvolutionaryOperator getChampMutation()

Returns:

the champMutation

getCODEC

public GeneticCODEC getCODEC()

Specified by:

getCODEC in interface EvolutionaryAlgorithm

Returns:

The CODEC that is used to transform between genome and phenome.

getEliteRate

public double getEliteRate()

Returns:

the eliteRate

getError

public double getError()

Specified by:

getError in interface EvolutionaryAlgorithm

Returns:

The current score. This value should either be minimized or maximized, depending on the score function.

getIteration

public int getIteration()

Specified by:

getIteration in interface EvolutionaryAlgorithm

Returns:

The current iteration number. Also sometimes referred to as generation or epoch.

getMaxIndividualSize

public int getMaxIndividualSize()

Specified by:

getMaxIndividualSize in interface EvolutionaryAlgorithm

Returns:

The maximum size an individual genome can be. This is an arbitrary number defined by the genome. Lower numbers are less complex.

getMaxTries

public int getMaxTries()

Specified by:

getMaxTries in interface EvolutionaryAlgorithm

Returns:

The maximum number to try certain genetic operations. This prevents endless loops.

getOldBestGenome

public Genome getOldBestGenome()

Returns:

the oldBestGenome

getOperators

public OperationList getOperators()

Specified by:

getOperators in interface EvolutionaryAlgorithm

Returns:

The operators.

getPopulation

public Population getPopulation()

Specified by:

getPopulation in interface EvolutionaryAlgorithm

Returns:

The population.

getRandomNumberFactory

public RandomFactory getRandomNumberFactory()

Returns:

the randomNumberFactory

getScoreAdjusters

public java.util.List<AdjustScore> getScoreAdjusters()

Specified by:

getScoreAdjusters in interface EvolutionaryAlgorithm

Returns:

The score adjusters. This allows bonuses and penalties to be applied for desirable or undesirable traits.

getScoreFunction

public CalculateScore getScoreFunction()

Specified by:

getScoreFunction in interface EvolutionaryAlgorithm

Returns:

The score function.

getSelection

public SelectionOperator getSelection()

Specified by:

getSelection in interface EvolutionaryAlgorithm

Returns:

The selection operator. Used to choose genomes.

getSelectionComparator

public GenomeComparator getSelectionComparator()

Get the comparator that is used to choose the "best" genome for selection, as opposed to the "true best". This uses the adjusted score, and not the score.

Specified by:

getSelectionComparator in interface EvolutionaryAlgorithm

Returns:

The selection comparator.

getShouldIgnoreExceptions

public boolean getShouldIgnoreExceptions()

Specified by:

getShouldIgnoreExceptions in interface EvolutionaryAlgorithm

Returns:

True if exceptions that occur during genetic operations should be ignored.

getSpeciation

public Speciation getSpeciation()

Specified by:

getSpeciation in interface EvolutionaryAlgorithm

Returns:

The speciation method.

getThreadCount

public int getThreadCount()

Specified by:

getThreadCount in interface MultiThreadable

Returns:

The number of threads to use, 0 to automatically determine based on core count.

isValidationMode

public boolean isValidationMode()

Specified by:

isValidationMode in interface EvolutionaryAlgorithm

Returns:

True if any genome validators should be applied.

iteration

public void iteration()

Perform a training iteration. Also called generations or epochs.

Specified by:

iteration in interface EvolutionaryAlgorithm

performShutdownTask

public void performShutdownTask()

Specified by:

performShutdownTask in interface EncogShutdownTask

reportError

public void reportError(java.lang.Throwable t)

Called by a thread to report an error.

Parameters:

t - The error reported.

setBestComparator

public void setBestComparator(GenomeComparator theComparator)

Set the comparator.

Specified by:

setBestComparator in interface EvolutionaryAlgorithm

Parameters:

theComparator - The comparator.

setChampMutation

public void setChampMutation(EvolutionaryOperator champMutation)

Parameters:

champMutation - the champMutation to set

setCODEC

public void setCODEC(GeneticCODEC theCodec)

Set the CODEC to use.

Parameters:

theCodec - The CODEC to use.

setEliteRate

public void setEliteRate(double eliteRate)

Parameters:

eliteRate - the eliteRate to set

setIteration

public void setIteration(int iteration)

Set the current iteration number.

Parameters:

iteration - The iteration number.

setMaxTries

public void setMaxTries(int maxTries)

Parameters:

maxTries - the maxTries to set

setPopulation

public void setPopulation(Population thePopulation)

Set the population.

Specified by:

setPopulation in interface EvolutionaryAlgorithm

Parameters:

thePopulation - The population.

setRandomNumberFactory

public void setRandomNumberFactory(RandomFactory randomNumberFactory)

Parameters:

randomNumberFactory - the randomNumberFactory to set

setSelection

public void setSelection(SelectionOperator selection)

Set the selection operator.

Specified by:

setSelection in interface EvolutionaryAlgorithm

Parameters:

selection - The selection operator.

setSelectionComparator

public void setSelectionComparator(GenomeComparator theComparator)

Set the comparator that is used to choose the "best" genome for selection, as opposed to the "true best". This uses the adjusted score, and not the score.

Specified by:

setSelectionComparator in interface EvolutionaryAlgorithm

Parameters:

theComparator - The selection comparator.

setShouldIgnoreExceptions

public void setShouldIgnoreExceptions(boolean b)

Determines if genetic operator exceptions should be ignored.

Specified by:

setShouldIgnoreExceptions in interface EvolutionaryAlgorithm

Parameters:

b - True if exceptions should be ignored.

setSpeciation

public void setSpeciation(Speciation speciation)

Set the speciation method.

Specified by:

setSpeciation in interface EvolutionaryAlgorithm

Parameters:

speciation - The speciation method.

setThreadCount

public void setThreadCount(int numThreads)

Set the number of threads to use.

Specified by:

setThreadCount in interface MultiThreadable

Parameters:

numThreads - The number of threads to use, or zero to automatically determine based on core count.

setValidationMode

public void setValidationMode(boolean validationMode)

Determine if the genomes should be validated. This takes more time but can help isolate a problem.

Specified by:

setValidationMode in interface EvolutionaryAlgorithm

Parameters:

validationMode - True, if validation mode is enabled.

getMaxOperationErrors

public int getMaxOperationErrors()

Returns:

the maxOperationErrors

setMaxOperationErrors

public void setMaxOperationErrors(int maxOperationErrors)

Parameters:

maxOperationErrors - the maxOperationErrors to set