/*
* Encog(tm) Core v2.5 - Java Version
* http://www.heatonresearch.com/encog/
* http://code.google.com/p/encog-java/
* Copyright 2008-2010 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.networks.synapse.neat;
import java.io.Serializable;
import java.util.ArrayList;
import java.util.List;
import org.encog.persist.annotations.EGAttribute;
import org.encog.persist.annotations.EGIgnore;
import org.encog.persist.annotations.EGReferenceable;
/**
* Implements a NEAT neuron. Neat neurons are of a specific type, defined by the
* NEATNeuronType enum. Usually NEAT uses a sigmoid activation function. The
* activation response is used to allow the slope of the sigmoid to be evolved.
*
* NeuroEvolution of Augmenting Topologies (NEAT) is a genetic algorithm for the
* generation of evolving artificial neural networks. It was developed by Ken
* Stanley while at The University of Texas at Austin.
*
* http://www.cs.ucf.edu/~kstanley/
*
*/
@EGReferenceable
public class NEATNeuron implements Serializable {
/**
* The serial id.
*/
private static final long serialVersionUID = -2815145950124389743L;
/**
* The activation response. This is evolved to allow NEAT to scale the slope
* of the activation function.
*/
@EGAttribute
private double activationResponse;
/**
* Inbound links to this neuron.
*/
private final List<NEATLink> inboundLinks = new ArrayList<NEATLink>();
/**
* The neuron id.
*/
@EGAttribute
private long neuronID;
/**
* The type of neuron this is.
*/
@EGAttribute
private NEATNeuronType neuronType;
/**
* The output from the neuron.
*/
@EGAttribute
private double output;
/**
* The outbound links for this neuron.
*/
private List<NEATLink> outputboundLinks = new ArrayList<NEATLink>();
/**
* The x-position of this neuron. Used to split links, as well as display.
*/
@EGAttribute
private int posX;
/**
* The y-position of this neuron. Used to split links, as well as display.
*/
@EGAttribute
private int posY;
/**
* The split value for X. Used to track splits.
*/
@EGAttribute
private double splitX;
/**
* The split value for Y. Used to track splits.
*/
@EGAttribute
private double splitY;
/**
* The sum activation.
*/
@EGIgnore
private double sumActivation;
/**
* Default constructor, used for persistance.
*/
public NEATNeuron() {
}
/**
* Construct a NEAT neuron.
*
* @param neuronType
* The type of neuron.
* @param neuronID
* The id of the neuron.
* @param splitY
* The split for y.
* @param splitX
* THe split for x.
* @param activationResponse
* The activation response.
*/
public NEATNeuron(final NEATNeuronType neuronType, final long neuronID,
final double splitY, final double splitX,
final double activationResponse) {
this.neuronType = neuronType;
this.neuronID = neuronID;
this.splitY = splitY;
this.splitX = splitX;
this.activationResponse = activationResponse;
posX = 0;
posY = 0;
output = 0;
sumActivation = 0;
}
/**
* @return the activation response.
*/
public double getActivationResponse() {
return activationResponse;
}
/**
* @return the inbound links.
*/
public List<NEATLink> getInboundLinks() {
return inboundLinks;
}
/**
* @return The neuron id.
*/
public long getNeuronID() {
return neuronID;
}
/**
* @return the neuron type.
*/
public NEATNeuronType getNeuronType() {
return neuronType;
}
/**
* @return The output from this neuron.
*/
public double getOutput() {
return output;
}
/**
* @return The outbound links.
*/
public List<NEATLink> getOutputboundLinks() {
return outputboundLinks;
}
/**
* @return The x position.
*/
public int getPosX() {
return posX;
}
/**
* @return The y position.
*/
public int getPosY() {
return posY;
}
/**
* @return The split x.
*/
public double getSplitX() {
return splitX;
}
/**
* @return The split y.
*/
public double getSplitY() {
return splitY;
}
/**
* @return The sum activation.
*/
public double getSumActivation() {
return sumActivation;
}
/**
* Set the output.
*
* @param output
* The output of the neuron.
*/
public void setOutput(final double output) {
this.output = output;
}
/**
* {@inheritDoc}
*/
@Override
public String toString() {
final StringBuilder result = new StringBuilder();
result.append("[NEATNeuron:id=");
result.append(neuronID);
result.append(",type=");
switch (neuronType) {
case Input:
result.append("I");
break;
case Output:
result.append("O");
break;
case Bias:
result.append("B");
break;
case Hidden:
result.append("H");
break;
default:
result.append("Unknown");
}
result.append("]");
return result.toString();
}
}