/*
* Encog(tm) Core v3.0 - Java Version
* http://www.heatonresearch.com/encog/
* http://code.google.com/p/encog-java/
* Copyright 2008-2011 Heaton Research, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
* For more information on Heaton Research copyrights, licenses
* and trademarks visit:
* http://www.heatonresearch.com/copyright
*/
package org.encog.ml.genetic;
import org.encog.ml.genetic.genome.Genome;
import org.encog.util.concurrency.EngineConcurrency;
import org.encog.util.concurrency.TaskGroup;
/**
* Provides a basic implementation of a genetic algorithm.
*/
public class BasicGeneticAlgorithm extends GeneticAlgorithm {
/**
* Is this the first iteration.
*/
private boolean first = true;
/**
* Modify the weight matrix and bias values based on the last call to
* calcError.
*
* @throws NeuralNetworkException
*/
@Override
public final void iteration() {
if (this.first) {
getPopulation().claim(this);
this.first = false;
}
final int countToMate = (int) (getPopulation().getPopulationSize()
* getPercentToMate());
final int offspringCount = countToMate * 2;
int offspringIndex = getPopulation().getPopulationSize()
- offspringCount;
final int matingPopulationSize = (int) (getPopulation()
.getPopulationSize() * getMatingPopulation());
final TaskGroup group = EngineConcurrency.getInstance()
.createTaskGroup();
// mate and form the next generation
for (int i = 0; i < countToMate; i++) {
final Genome mother = getPopulation().getGenomes().get(i);
final int fatherInt = (int) (Math.random() * matingPopulationSize);
final Genome father = getPopulation().getGenomes().get(fatherInt);
final Genome child1 = getPopulation().getGenomes().get(
offspringIndex);
final Genome child2 = getPopulation().getGenomes().get(
offspringIndex + 1);
final MateWorker worker = new MateWorker(mother, father, child1,
child2);
if( this.isMultiThreaded() ) {
EngineConcurrency.getInstance().processTask(worker, group);
} else {
worker.run();
}
offspringIndex += 2;
}
if( this.isMultiThreaded() ) {
group.waitForComplete();
}
// sort the next generation
getPopulation().sort();
}
}