/*
* Encog(tm) Core v3.3 - Java Version
* http://www.heatonresearch.com/encog/
* https://github.com/encog/encog-java-core
* Copyright 2008-2014 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);
}
}