/* * 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(); } }