BasicEA (Encog Core 3.3.0 API)

java.lang.Object
- org.encog.ml.ea.train.basic.BasicEA

All Implemented Interfaces:

Serializable, EncogShutdownTask, EvolutionaryAlgorithm, MultiThreadable

Direct Known Subclasses:

TrainEA
```
public class BasicEA
extends Object
implements EvolutionaryAlgorithm, MultiThreadable, EncogShutdownTask, 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.

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

Method Summary

Methods
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, 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()`
`RuleHolder`	`getRules()`
`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(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`	`setRules(RuleHolder rules)` Set the rules holder to use.
`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
clone, equals, finalize, 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,
                            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
  - getRules
```
public RuleHolder getRules()
```
    Specified by:
    
    getRules in interface EvolutionaryAlgorithm
    
    Returns:
    the rules
  - getScoreAdjusters
```
public 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(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
  - setRules
```
public void setRules(RuleHolder rules)
```
    Description copied from interface: EvolutionaryAlgorithm
    
    Set the rules holder to use.
    
    Specified by:
    
    setRules in interface EvolutionaryAlgorithm
    
    Parameters:
    rules - the rules 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

Class BasicEA

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

BasicEA

Method Detail

calculateScoreAdjustment

addChild

addOperation

addScoreAdjuster

calculateScore

finishTraining

getBestComparator

getBestGenome

getChampMutation

getCODEC

getEliteRate

getError

getIteration

getMaxIndividualSize

getMaxTries

getOldBestGenome

getOperators

getPopulation

getRandomNumberFactory

getRules

getScoreAdjusters

getScoreFunction

getSelection

getSelectionComparator

getShouldIgnoreExceptions

getSpeciation

getThreadCount

isValidationMode

iteration

performShutdownTask

reportError

setBestComparator

setChampMutation

setCODEC

setEliteRate

setIteration

setMaxTries

setPopulation

setRandomNumberFactory

setRules

setSelection

setSelectionComparator

setShouldIgnoreExceptions

setSpeciation

setThreadCount

setValidationMode

getMaxOperationErrors

setMaxOperationErrors