gov.sandia.cognition.learning.algorithm.genetic

Class ParallelizedGeneticAlgorithm<CostParametersType,GenomeType>

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm

gov.sandia.cognition.algorithm.AbstractAnytimeAlgorithm<ResultType>

gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner<CostParametersType,GenomeType>

gov.sandia.cognition.learning.algorithm.genetic.GeneticAlgorithm<CostParametersType,GenomeType>

gov.sandia.cognition.learning.algorithm.genetic.ParallelizedGeneticAlgorithm<CostParametersType,GenomeType>

Type Parameters:

GenomeType - Type of genome used to represent a single element in the genetic population. For example, a Vector.

CostParametersType - Type of parameters that the cost function takes. For example, Collection<InputOutputPairs>.

All Implemented Interfaces:

AnytimeAlgorithm<GenomeType>, IterativeAlgorithm, MeasurablePerformanceAlgorithm, ParallelAlgorithm, StoppableAlgorithm, AnytimeBatchLearner<CostParametersType,GenomeType>, BatchCostMinimizationLearner<CostParametersType,GenomeType>, BatchLearner<CostParametersType,GenomeType>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

public class ParallelizedGeneticAlgorithm<CostParametersType,GenomeType>
extends GeneticAlgorithm<CostParametersType,GenomeType>
implements ParallelAlgorithm

This is a parallel implementation of the genetic algorithm. The default is to use n-1 available cores/hyperthreads on a machine and spread the cost function evaluations across these computational units.

Author:

cewarr

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
protected class	ParallelizedGeneticAlgorithm.EvaluateGenome Callable task for the evaluate() method.

Field Summary

Fields inherited from class gov.sandia.cognition.learning.algorithm.genetic.GeneticAlgorithm

DEFAULT_MAX_ITERATIONS

Fields inherited from class gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner

data, keepGoing

Fields inherited from class gov.sandia.cognition.algorithm.AbstractAnytimeAlgorithm

maxIterations

Fields inherited from class gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm

DEFAULT_ITERATION, iteration

Constructor Summary

Constructors

Constructor and Description
ParallelizedGeneticAlgorithm() Default constructor
ParallelizedGeneticAlgorithm(java.util.Collection<GenomeType> initialPopulation, Reproducer<GenomeType> reproducer, CostFunction<? super GenomeType,? super CostParametersType> cost, java.util.concurrent.ThreadPoolExecutor threadPool)
ParallelizedGeneticAlgorithm(java.util.Collection<GenomeType> initialPopulation, Reproducer<GenomeType> reproducer, CostFunction<? super GenomeType,? super CostParametersType> cost, java.util.concurrent.ThreadPoolExecutor threadPool, int maxIterations, int maxIterationsWithoutImprovement)

Method Summary

Modifier and Type	Method and Description
protected void	createEvaluationTasks(java.util.Collection<GenomeType> population) Creates the evaluation tasks to execute in parallel.
protected java.util.ArrayList<EvaluatedGenome<GenomeType>>	evaluatePopulation(java.util.Collection<GenomeType> population) Converts a population of genomes into evaluated genomes.
int	getNumThreads() Getter for #threads
java.util.concurrent.ThreadPoolExecutor	getThreadPool() Getter for threadPool
void	setThreadPool(java.util.concurrent.ThreadPoolExecutor threadPool) Setter for threadPool

Methods inherited from class gov.sandia.cognition.learning.algorithm.genetic.GeneticAlgorithm

cleanupAlgorithm, getBestSoFar, getCostFunction, getInitialPopulation, getIterationsWithoutImprovement, getMaxIterationsWithoutImprovement, getPerformance, getPopulation, getReproducer, getResult, initializeAlgorithm, searchForBetter, setBestSoFar, setCostFunction, setInitialPopulation, setIterationsWithoutImprovement, setMaxIterationsWithoutImprovement, setPopulation, setReproducer, step

Methods inherited from class gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner

clone, getData, getKeepGoing, learn, setData, setKeepGoing, stop

Methods inherited from class gov.sandia.cognition.algorithm.AbstractAnytimeAlgorithm

getMaxIterations, isResultValid, setMaxIterations

Methods inherited from class gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm

addIterativeAlgorithmListener, fireAlgorithmEnded, fireAlgorithmStarted, fireStepEnded, fireStepStarted, getIteration, getListeners, removeIterativeAlgorithmListener, setIteration, setListeners

Methods inherited from class java.lang.Object

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

Methods inherited from interface gov.sandia.cognition.util.CloneableSerializable

clone

Methods inherited from interface gov.sandia.cognition.learning.algorithm.BatchCostMinimizationLearner

learn

Methods inherited from interface gov.sandia.cognition.algorithm.AnytimeAlgorithm

getMaxIterations, setMaxIterations

Methods inherited from interface gov.sandia.cognition.algorithm.IterativeAlgorithm

addIterativeAlgorithmListener, getIteration, removeIterativeAlgorithmListener

Methods inherited from interface gov.sandia.cognition.algorithm.StoppableAlgorithm

isResultValid

Constructor Detail

ParallelizedGeneticAlgorithm

public ParallelizedGeneticAlgorithm()

Default constructor

ParallelizedGeneticAlgorithm

public ParallelizedGeneticAlgorithm(java.util.Collection<GenomeType> initialPopulation,
                                    Reproducer<GenomeType> reproducer,
                                    CostFunction<? super GenomeType,? super CostParametersType> cost,
                                    java.util.concurrent.ThreadPoolExecutor threadPool)

Parameters:

initialPopulation - The initial population to start the algorithm

reproducer - The reproduction method to use.

cost - The cost function for genomes.

threadPool - Thread pool to use for parallelization

ParallelizedGeneticAlgorithm

public ParallelizedGeneticAlgorithm(java.util.Collection<GenomeType> initialPopulation,
                                    Reproducer<GenomeType> reproducer,
                                    CostFunction<? super GenomeType,? super CostParametersType> cost,
                                    java.util.concurrent.ThreadPoolExecutor threadPool,
                                    int maxIterations,
                                    int maxIterationsWithoutImprovement)

Parameters:

initialPopulation - The initial population to start the algorithm

reproducer - The reproduction method to use.

cost - The cost function for genomes.

threadPool - Thread pool to use for parallelization

maxIterations - The maximum number of iterations to run.

maxIterationsWithoutImprovement - The maximum number of iterations to go without improvement before stopping.

Method Detail

getThreadPool

public java.util.concurrent.ThreadPoolExecutor getThreadPool()

Getter for threadPool

Specified by:

getThreadPool in interface ParallelAlgorithm

Returns:

Thread pool used to parallelize the computation

setThreadPool

public void setThreadPool(java.util.concurrent.ThreadPoolExecutor threadPool)

Setter for threadPool

Specified by:

setThreadPool in interface ParallelAlgorithm

Parameters:

threadPool - Thread pool used to parallelize the computation

getNumThreads

public int getNumThreads()

Getter for #threads

Specified by:

getNumThreads in interface ParallelAlgorithm

Returns:

#threads

createEvaluationTasks

protected void createEvaluationTasks(java.util.Collection<GenomeType> population)

Creates the evaluation tasks to execute in parallel.

Parameters:

population - The population to create tasks for.

evaluatePopulation

protected java.util.ArrayList<EvaluatedGenome<GenomeType>> evaluatePopulation(java.util.Collection<GenomeType> population)

Converts a population of genomes into evaluated genomes.

Overrides:

evaluatePopulation in class GeneticAlgorithm<CostParametersType,GenomeType>

Parameters:

population - The population of genomes to evaluate.

Returns:

A population of evaluated genomes.