/* * 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.hyperneat; import java.util.List; import java.util.Random; import org.encog.engine.network.activation.ActivationBipolarSteepenedSigmoid; import org.encog.engine.network.activation.ActivationClippedLinear; import org.encog.engine.network.activation.ActivationFunction; import org.encog.engine.network.activation.ActivationGaussian; import org.encog.engine.network.activation.ActivationSIN; 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.NEATNeuronGene; import org.encog.util.obj.ChooseObject; /** * A HyperNEAT genome. */ public class HyperNEATGenome extends NEATGenome { /** * A HyperNEAT genome. */ private static final long serialVersionUID = 1L; /** * Build the CPPN activation functions. * @param activationFunctions The activation functions collection to add to. */ public static void buildCPPNActivationFunctions( final ChooseObject<ActivationFunction> activationFunctions) { activationFunctions.add(0.25, new ActivationClippedLinear()); activationFunctions.add(0.25, new ActivationBipolarSteepenedSigmoid()); activationFunctions.add(0.25, new ActivationGaussian()); activationFunctions.add(0.25, new ActivationSIN()); activationFunctions.finalizeStructure(); } /** * Construct a HyperNEAT genome. */ public HyperNEATGenome() { } public HyperNEATGenome(final HyperNEATGenome other) { super(other); } /** * Construct a HyperNEAT genome from a list of neurons and links. * @param neurons The neurons. * @param links The links. * @param inputCount The input count. * @param outputCount The output count. */ public HyperNEATGenome(final List<NEATNeuronGene> neurons, final List<NEATLinkGene> links, final int inputCount, final int outputCount) { super(neurons, links, inputCount, outputCount); } /** * Construct a random HyperNEAT genome. * @param rnd Random number generator. * @param pop The target population. * @param inputCount The input count. * @param outputCount The output count. * @param connectionDensity The connection densitoy, 1.0 for fully connected. */ public HyperNEATGenome(final Random rnd, final NEATPopulation pop, final int inputCount, final int outputCount, final double connectionDensity) { super(rnd, pop, inputCount, outputCount, connectionDensity); } }