/*
* Encog(tm) Core v3.4 - Java Version
* http://www.heatonresearch.com/encog/
* https://github.com/encog/encog-java-core
* Copyright 2008-2016 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.neural.neat.training.opp;
import java.io.Serializable;
import java.util.List;
import java.util.Random;
import org.encog.ml.ea.genome.Genome;
import org.encog.neural.neat.NEATPopulation;
import org.encog.neural.neat.training.NEATGenome;
import org.encog.neural.neat.training.NEATLinkGene;
import org.encog.neural.neat.training.opp.links.MutateLinkWeight;
import org.encog.neural.neat.training.opp.links.SelectLinks;
/**
* Mutate the weights of a genome. A method is select the links for mutation.
* Another method should also be provided for the actual mutation.
*
* -----------------------------------------------------------------------------
* http://www.cs.ucf.edu/~kstanley/ Encog's NEAT implementation was drawn from
* the following three Journal Articles. For more complete BibTeX sources, see
* NEATNetwork.java.
*
* Evolving Neural Networks Through Augmenting Topologies
*
* Generating Large-Scale Neural Networks Through Discovering Geometric
* Regularities
*
* Automatic feature selection in neuroevolution
*/
public class NEATMutateWeights extends NEATMutation implements Serializable {
/**
* The method used to select the links to mutate.
*/
private final SelectLinks linkSelection;
/**
* The method used to mutate the selected links.
*/
private final MutateLinkWeight weightMutation;
/**
* Construct a weight mutation operator.
* @param theLinkSelection The method used to choose the links for mutation.
* @param theWeightMutation The method used to actually mutate the weights.
*/
public NEATMutateWeights(final SelectLinks theLinkSelection,
final MutateLinkWeight theWeightMutation) {
this.linkSelection = theLinkSelection;
this.weightMutation = theWeightMutation;
}
/**
* @return The method used to select links for mutation.
*/
public SelectLinks getLinkSelection() {
return this.linkSelection;
}
/**
* @return The method used to mutate the weights.
*/
public MutateLinkWeight getWeightMutation() {
return this.weightMutation;
}
/**
* {@inheritDoc}
*/
@Override
public void performOperation(final Random rnd, final Genome[] parents,
final int parentIndex, final Genome[] offspring,
final int offspringIndex) {
final NEATGenome target = obtainGenome(parents, parentIndex, offspring,
offspringIndex);
final double weightRange = ((NEATPopulation)getOwner().getPopulation()).getWeightRange();
final List<NEATLinkGene> list = this.linkSelection.selectLinks(rnd,
target);
for (final NEATLinkGene gene : list) {
this.weightMutation.mutateWeight(rnd, gene, weightRange);
}
}
/**
* {@inheritDoc}
*/
@Override
public String toString() {
final StringBuilder result = new StringBuilder();
result.append("[");
result.append(this.getClass().getSimpleName());
result.append(":sel=");
result.append(this.linkSelection.toString());
result.append(",mutate=");
result.append(this.weightMutation.toString());
result.append("]");
return result.toString();
}
}