/* * Artificial Intelligence for Humans * Volume 2: Nature Inspired Algorithms * Java Version * http://www.aifh.org * http://www.jeffheaton.com * * Code repository: * https://github.com/jeffheaton/aifh * * Copyright 2014 by Jeff Heaton * * 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 com.heatonresearch.aifh.genetic.trees; import com.heatonresearch.aifh.evolutionary.genome.Genome; import com.heatonresearch.aifh.evolutionary.opp.EvolutionaryOperator; import com.heatonresearch.aifh.evolutionary.train.EvolutionaryAlgorithm; import com.heatonresearch.aifh.randomize.GenerateRandom; /** * Create a child tree as a mutation of the parent. Do not modify the parent. */ public class MutateTree implements EvolutionaryOperator { /** * The owner. */ private EvolutionaryAlgorithm owner; /** * The maximum length of a branch to graft. */ private int maxGraftLength; /** * Construct the tree mutation object. * @param theMaxGraftLength The maximum graft length. */ public MutateTree(int theMaxGraftLength) { this.maxGraftLength = Math.max(1, theMaxGraftLength); } /** * {@inheritDoc} */ @Override public void init(final EvolutionaryAlgorithm theOwner) { this.owner = theOwner; } /** * {@inheritDoc} */ @Override public int offspringProduced() { return 1; } /** * {@inheritDoc} */ @Override public int parentsNeeded() { return 1; } /** * {@inheritDoc} */ @Override public void performOperation(final GenerateRandom rnd, final Genome[] parents, final int parentIndex, final Genome[] offspring, final int offspringIndex) { TreeGenome parent1 = (TreeGenome) parents[parentIndex]; EvaluateTree eval = parent1.getEvaluator(); TreeGenome off1 = (TreeGenome) this.owner.getPopulation().getGenomeFactory().factor(parent1); RandomNodeResult off1Point = eval.sampleRandomNode(rnd, off1.getRoot()); int len = rnd.nextInt(1, this.maxGraftLength + 1); TreeGenomeNode randomSequence = eval.grow(rnd, len); if (off1Point.getParent() == null) { off1.setRoot(randomSequence); } else { int idx = off1Point.getParent().getChildren().indexOf(off1Point.getChild()); off1Point.getParent().getChildren().set(idx, randomSequence); } offspring[0] = off1; } }