jaga.control
Class NoisyPIM

java.lang.Object
  |
  +--jaga.control.NoisyPIM

All Implemented Interfaces:

InteractionModel, java.io.Serializable

public class NoisyPIM

extends java.lang.Object

implements InteractionModel

Noisy Property Interaction Model is like NoisyIM yet it averages properties over many evaluations. For now we assume all individuals have constant number of properties. IMPORTANT: The Random number generator will be re-initialized whenever this class is serialized. In a setup with many concurrent clients we don't want all to be testing exactly the same noise levels. This can be changed by removing the transient property from the rnd variable.

See Also:

Serialized Form

Field Summary

static int	AVERAGE
static int	MAXIMUM
static java.lang.String[]	methodStrings
static int	MINIMUM

Constructor Summary

NoisyPIM(InteractionModel im, Deployment dep, ConfigurableRandomInputExperiment cr, int[] numProps)
Creates new NoisyIM

NoisyPIM(InteractionModel im, Deployment dep, ConfigurableRandomInputExperiment cr, int[] numProps, int evals)

NoisyPIM(InteractionModel im, Deployment dep, ConfigurableRandomInputExperiment cr, int[] numProps, int evals, int method)

NoisyPIM(InteractionModel im, Deployment dep, int[] numProps)
Creates new NoisyIM

NoisyPIM(InteractionModel im, Deployment dep, int[] numProps, int evals)

NoisyPIM(InteractionModel im, Deployment dep, int[] numProps, int evals, int method)

Method Summary

double[]	evaluate(Genotype[] inds) Evaluates these individuals using the deployment and experiments and procedure of this model.
double[]	evaluateNext() Should be same as calling evaluate( pickIndividuals() );
int	evaluationsPerGeneration()
void	evolve() Evolves to the next generation of all/some of the populations involved.
Genotype	getMaxFitness()
Genotype[]	getNextIndividuals() Picks a number of individuals to be evaluated next.
int	getNumEvolvers()
Population[]	getPopulations()
islandev.SnapshotPainter	getSnapshotPainter()
Genotype[]	pickIndividuals()
void	setPopulations(Population[] pops) Sets the populations of the evolvers to be these
java.lang.String	toString()

Methods inherited from class java.lang.Object

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

Field Detail

MINIMUM

public static final int MINIMUM

MAXIMUM

public static final int MAXIMUM

AVERAGE

public static final int AVERAGE

methodStrings

public static final java.lang.String[] methodStrings

Constructor Detail

NoisyPIM

public NoisyPIM(InteractionModel im,
                Deployment dep,
                int[] numProps,
                int evals,
                int method)

NoisyPIM

public NoisyPIM(InteractionModel im,
                Deployment dep,
                int[] numProps,
                int evals)

NoisyPIM

public NoisyPIM(InteractionModel im,
                Deployment dep,
                int[] numProps)

Creates new NoisyIM

NoisyPIM

public NoisyPIM(InteractionModel im,
                Deployment dep,
                ConfigurableRandomInputExperiment cr,
                int[] numProps,
                int evals,
                int method)

NoisyPIM

public NoisyPIM(InteractionModel im,
                Deployment dep,
                ConfigurableRandomInputExperiment cr,
                int[] numProps,
                int evals)

NoisyPIM

public NoisyPIM(InteractionModel im,
                Deployment dep,
                ConfigurableRandomInputExperiment cr,
                int[] numProps)

Creates new NoisyIM

Method Detail

evaluationsPerGeneration

public int evaluationsPerGeneration()

Specified by:

evaluationsPerGeneration in interface InteractionModel

Returns:

the number of evaluations per generation to be performed

getNextIndividuals

public Genotype[] getNextIndividuals()

Picks a number of individuals to be evaluated next. These individuals can be from any of the populations as long as there is a standard interface between the caller and this method implementation as to where each come from. Example: may be first element a pac-man, and five others albl

Specified by:

getNextIndividuals in interface InteractionModel

evaluate

public double[] evaluate(Genotype[] inds)

Evaluates these individuals using the deployment and experiments and procedure of this model. Assume propSums empty, so leave empty when leaving.

Specified by:

evaluate in interface InteractionModel

Returns:

an array of the fitnesses of the individuals.

evaluateNext

public double[] evaluateNext()

Should be same as calling evaluate( pickIndividuals() );

Specified by:

evaluateNext in interface InteractionModel

Returns:

an array of the fitnesses of the individuals.

evolve

public void evolve()

Evolves to the next generation of all/some of the populations involved. Next set of seeds is generated.

Specified by:

evolve in interface InteractionModel

getNumEvolvers

public int getNumEvolvers()

Specified by:

getNumEvolvers in interface InteractionModel

Returns:

the number of evolvers (ie. populations) acting in this model.

pickIndividuals

public Genotype[] pickIndividuals()

Specified by:

pickIndividuals in interface InteractionModel

Returns:

randomly picked individuals from the evolvers.

getPopulations

public Population[] getPopulations()

Specified by:

getPopulations in interface InteractionModel

Returns:

the current populations of the evolvers.

getSnapshotPainter

public islandev.SnapshotPainter getSnapshotPainter()

Specified by:

getSnapshotPainter in interface InteractionModel

Returns:

String displaying performance of fittest individual.

getMaxFitness

public Genotype getMaxFitness()

Specified by:

getMaxFitness in interface InteractionModel

Returns:

The maximum fitness a genotype can achieve. ie. when evolution will stop

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object

setPopulations

public void setPopulations(Population[] pops)

Sets the populations of the evolvers to be these

Specified by:

setPopulations in interface InteractionModel