// Distributed Decision making system framework
// Copyright (c) 2014, Jordi Coll Corbilla
// All rights reserved.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are met:
//
// - Redistributions of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
// - Redistributions in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
// - Neither the name of this library nor the names of its contributors may be
// used to endorse or promote products derived from this software without
// specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
// POSSIBILITY OF SUCH DAMAGE.
package ddm.behaviours;
import jade.content.ContentElement;
import jade.content.lang.Codec;
import jade.content.lang.sl.SLCodec;
import jade.content.onto.Ontology;
import jade.content.onto.basic.Action;
import jade.core.behaviours.OneShotBehaviour;
import jade.lang.acl.ACLMessage;
import ddm.agents.ClassifierAgent;
import ddm.data.DataSetGenerator;
import ddm.factory.classifiers.ClassifierInstance;
import ddm.ontology.ClassificationResult;
import ddm.ontology.ClassifierOntology;
import ddm.ontology.DataInstance;
/**
*
* @author jordi Corbilla
* Behaviour to handle the data the classifier needs to process.
* Once the agent has processed the data, it sends the result back to the manager.
*/
@SuppressWarnings("serial")
public class HandleDataToClassifyBehaviour extends OneShotBehaviour {
private ClassifierAgent myAgent;
private ACLMessage request;
private ClassifierInstance classifier;
private Codec codec = new SLCodec();
private Ontology ontology = ClassifierOntology.getInstance();
public HandleDataToClassifyBehaviour(ClassifierAgent a, ACLMessage request) {
super(a);
this.myAgent = a;
this.request = request;
this.classifier = a.getClassifier();
}
@Override
public void action() {
try {
ContentElement content = myAgent.getContentManager().extractContent(request);
DataInstance di = (DataInstance)((Action)content).getAction();
DataSetGenerator.GenerateDataFileForClassifier(myAgent.getLocalName(), myAgent.getHeader(), di);
this.classifier.setDataFile(myAgent.getConfiguration()
.getApplicationPath() + myAgent.getLocalName() + "_DataRepository.arff");
this.classifier.ClassifyInstances();
ACLMessage reply = request.createReply();
reply.setPerformative(ACLMessage.PROPOSE);
reply.setLanguage(codec.getName());
reply.setOntology(ontology.getName());
try {
ClassificationResult cr = new ClassificationResult();
cr.setDuration(classifier.getDurationTimeMs());
cr.setName(myAgent.getLocalName());
cr.setType(this.classifier.type());
cr.setNumCorrect(this.classifier.getCorrectIntances());
cr.setPercentage(this.classifier.getPercentage());
cr.setTrainingSize(myAgent.getTrainingSize());
cr.setInstanceValue(this.classifier.getInstanceValue());
cr.setPredictedInstanceValue(this.classifier.getPredictedInstanceValue());
cr.setInstanceClassification(this.classifier.getInstanceClassification());
cr.setInstancePredictedValue(this.classifier.getInstancePredictedClass());
myAgent.getContentManager().fillContent(reply, new Action(request.getSender(), cr));
reply.addReceiver(request.getSender());
myAgent.send(reply);
}
catch (Exception ex) { ex.printStackTrace();
}
}
catch(Exception ex) { ex.printStackTrace(); }
}
}