// 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(); } } }