Examples of Learner

aima.core.learning.framework.Learner
@author Ravi Mohan
com.digitalpebble.classification.Learner
com.sleepycat.je.rep.elections.Learner
The Learner agent. It runs in its own dedicated thread, listening for messages announcing the results of elections. The Learner in turn invokes Listeners within the process to propagate the result.
statechum.analysis.learning.Learner
statechum.analysis.learning.observers.Learner

Examples of statechum.analysis.learning.Learner

    // now sanity checking on the plus and minus sets
    for(String [] path:plus)
      assert AbstractOracle.USER_ACCEPTED == expected.paths.tracePathPrefixClosed(AbstractLearnerGraph.buildList(Arrays.asList(path),testConfig));
    for(String [] path:minus)
      assert AbstractOracle.USER_ACCEPTED != expected.paths.tracePathPrefixClosed(AbstractLearnerGraph.buildList(Arrays.asList(path),testConfig));
    Learner l = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,testConfig,null,null))
    {
      @Override
      public Pair<Integer,String> CheckWithEndUser(
          @SuppressWarnings("unused")  LearnerGraph model,
          List<Label> question, @SuppressWarnings("unused") int responseForNoRestart,
          @SuppressWarnings("unused") List<Boolean> acceptedElements,
          @SuppressWarnings("unused") PairScore pairBeingMerged,
          @SuppressWarnings("unused")  final Object [] moreOptions)
      {
        return new Pair<Integer,String>(expected.paths.tracePathPrefixClosed(question),null);
      }
    };
    testConfig.setLearnerIdMode(IDMode.POSITIVE_NEGATIVE);
    ByteArrayOutputStream logStream = new ByteArrayOutputStream();
    RecordProgressDecorator recorder = new RecordProgressDecorator(l,logStream,1,testConfig,useZip);
    Collection<List<Label>> testSet = new LinkedList<List<Label>>();
    recorder.writeLearnerEvaluationData(new LearnerEvaluationConfiguration(expected, testSet, testConfig, null, null));
    LearnerGraph learntStructureA = recorder.learnMachine(buildSet(plus,testConfig), buildSet(minus,testConfig));
    
    //System.out.println("compression rate: "+recorder.getCompressionRate());
    //System.out.println(logStream.toString()+"============");
    //System.out.println(logStream.toByteArray().length);
    LearnerGraph learntMachineNoRejects = new LearnerGraph(testConfig);
    AbstractPathRoutines.removeRejectStates(learntStructureA,learntMachineNoRejects);
    Assert.assertNull(WMethod.checkM(learntMachineNoRejects, expected));
    
    switch(kind)
    {
      case RECORDERTEST_SS:
      {// matching two simulators
        final LearnerSimulator 
          simulator = new LearnerSimulator(new ByteArrayInputStream(logStream.toByteArray()),useZip),
          simulator2 = new LearnerSimulator(new ByteArrayInputStream(logStream.toByteArray()),useZip);
        
        LearnerEvaluationConfiguration eval1 = simulator.readLearnerConstructionData(testConfig);
        Assert.assertNull(WMethod.checkM(expected, eval1.graph));
        Assert.assertEquals(testSet, eval1.testSet);
        Assert.assertEquals(expected.config, testConfig);
        LearnerEvaluationConfiguration eval2 = simulator2.readLearnerConstructionData(testConfig);
        Assert.assertNull(WMethod.checkM(expected, eval2.graph));
        Assert.assertEquals(testSet, eval2.testSet);
        Assert.assertEquals(expected.config, testConfig);
        
        new Test_LearnerComparator(simulator,simulator2,true).learnMachine(buildSet(plus,testConfig), buildSet(minus,testConfig));
        break;
      }
      
      case RECORDERTEST_SL:
      {// now a simulator to a learner
        final LearnerSimulator simulator = new LearnerSimulator(new ByteArrayInputStream(logStream.toByteArray()),useZip);
        LearnerEvaluationConfiguration eval1 = simulator.readLearnerConstructionData(testConfig);
        Assert.assertNull(WMethod.checkM(expected, eval1.graph));
        Assert.assertEquals(testSet, eval1.testSet);
        Assert.assertEquals(expected.config, testConfig);
  
        Learner learner2 = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,expected.config,null,null))
        {
          @Override
          public Pair<Integer,String> CheckWithEndUser(
              @SuppressWarnings("unused")  LearnerGraph model,
              List<Label> question, @SuppressWarnings("unused") int responseForNoRestart, 
              @SuppressWarnings("unused") List<Boolean> acceptedElements,
              @SuppressWarnings("unused") PairScore pairBeingMerged,
              @SuppressWarnings("unused")  final Object [] moreOptions)
          {
            return new Pair<Integer,String>(expected.paths.tracePathPrefixClosed(question),null);
          }
        };
        new Test_LearnerComparator(learner2,simulator,true).learnMachine(buildSet(plus,testConfig), buildSet(minus,testConfig));
        break;
      }


      case RECORDERTEST_LL:
      {// now two learners
        Learner learnerA = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,testConfig,null,null))
        {
          @Override
          public Pair<Integer,String> CheckWithEndUser(
              @SuppressWarnings("unused")  LearnerGraph model,
              List<Label> question, @SuppressWarnings("unused") int responseForNoRestart,
              @SuppressWarnings("unused") List<Boolean> acceptedElements,
              @SuppressWarnings("unused") PairScore pairBeingMerged,
              @SuppressWarnings("unused")  final Object [] moreOptions)
          {
            return new Pair<Integer,String>(expected.paths.tracePathPrefixClosed(question),null);
          }
        };
        Learner learnerB = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,testConfig,null,null))
        {
          @Override
          public Pair<Integer,String> CheckWithEndUser(
              @SuppressWarnings("unused")  LearnerGraph model,
              List<Label> question, @SuppressWarnings("unused") int responseForNoRestart,

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Examples of statechum.analysis.learning.Learner

                    innerLearner = new ErlangOracleLearner(ErlangOracleVisualiser.this, conf);
                } else {
                    innerLearner = new ErlangOracleLearner(ErlangOracleVisualiser.this, conf);// at this point ifthenSequences will always be null.
                }
                innerLearner.addObserver(ErlangOracleVisualiser.this);
                Learner mainDecorator = new AutoAnswers(innerLearner);
                if (conf.labelDetails != null) {
                    mainDecorator = new SmtLearnerDecorator(mainDecorator, conf.labelDetails);
                }
                if (whomToNotify != null) {
                    whomToNotify.threadStarted();
                }
                LearnerGraph initGraph = mainDecorator.init(sPlus, sMinus);
                initGraph.getLayoutOptions().showNegatives = false;
                LearnerGraph graph = mainDecorator.learnMachine();
                if (graph != null) {
                  try
                  {
                    DirectedSparseGraph learnt = graph.pathroutines.getGraph();
                      if (conf.config.isGenerateTextOutput()) {

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Examples of statechum.analysis.learning.Learner

                    innerLearner = new ErlangOracleLearner(ErlangOracleVisualiser.this, conf);
                } else {
                    innerLearner = new ErlangOracleLearner(ErlangOracleVisualiser.this, conf);// at this point ifthenSequences will always be null.
                }
                innerLearner.addObserver(ErlangOracleVisualiser.this);
                Learner mainDecorator = new AutoAnswers(innerLearner);
                if (conf.labelDetails != null) {
                    mainDecorator = new SmtLearnerDecorator(mainDecorator, conf.labelDetails);
                }
                if (whomToNotify != null) {
                    whomToNotify.threadStarted();
                }
                LearnerGraph initGraph = mainDecorator.init(sPlus, sMinus);
                initGraph.getLayoutOptions().showNegatives = false;
                LearnerGraph graph = mainDecorator.learnMachine();
                if (graph != null) {
                  try
                  {
                    DirectedSparseGraph learnt = graph.pathroutines.getGraph();
                      if (conf.config.isGenerateTextOutput()) {

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Examples of statechum.analysis.learning.Learner

    { 
      initial.plus.addAll(evalData.labelDetails.getSPlus());initial.minus.addAll(evalData.labelDetails.getSMinus());
    }
    simulator.setNextElement(nextElement);


    Learner learner2 = null;


    if (logFileName.contains(Configuration.LEARNER.LEARNER_BLUEFRINGE_DEC2007.name()))
    {// have to patch the learner.
      
      learner2 = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,evalData.config,null,null))

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Examples of statechum.analysis.learning.Learner


    public static void main(String[] args) {
        QSMTool tool = new QSMTool();
        tool.loadConfig(args[0]);
        if (tool.showLTL) {
            Learner l = new RPNIUniversalLearner(null, tool.learnerInitConfiguration);
            LTL_to_ba ba = new LTL_to_ba(tool.learnerInitConfiguration.config, tool.learnerInitConfiguration.getLabelConverter());
            if (ba.ltlToBA(tool.learnerInitConfiguration.ifthenSequences, l.init(tool.sPlus, tool.sMinus), true,
                    GlobalConfiguration.getConfiguration().getProperty(GlobalConfiguration.G_PROPERTIES.LTL2BA))) {
                try {
                    LearnerGraph graph = Transform.ltlToIfThenAutomaton(ba.getLTLgraph().pathroutines.buildDeterministicGraph());
                    DirectedSparseGraph gr = graph.pathroutines.getGraph();
                    PathRoutines.convertPairAssociationsToTransitions(gr, graph, tool.learnerInitConfiguration.config,tool.learnerInitConfiguration.getLabelConverter());

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Examples of statechum.analysis.learning.Learner

    for(String [] path:plus)
      assert AbstractOracle.USER_ACCEPTED == expected.paths.tracePathPrefixClosed(AbstractLearnerGraph.buildList(Arrays.asList(path),config,getLabelConverter()));
    for(String [] path:minus)
      assert AbstractOracle.USER_ACCEPTED != expected.paths.tracePathPrefixClosed(AbstractLearnerGraph.buildList(Arrays.asList(path),config,getLabelConverter()));
    // Visualiser.getVisualiser()
    Learner l = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,testConfig,null,null))
    {
      @Override
      public LearnerGraph MergeAndDeterminize(LearnerGraph original, StatePair pair) 
      {
        // Check that compatibility score computation gives the same response as if we did merge and computed a difference between the number of states.
        ScoreMode origScore = original.config.getLearnerScoreMode();original.config.setLearnerScoreMode(ScoreMode.COMPATIBILITY);
        long compatibilityScore = original.pairscores.computePairCompatibilityScore(pair);
        original.config.setLearnerScoreMode(origScore);
        LearnerGraph outcome = super.MergeAndDeterminize(original, pair);
        Assert.assertEquals(compatibilityScore+1,original.getStateNumber()-outcome.getStateNumber());
        return outcome;
      }


      @Override
      public Pair<Integer,String> CheckWithEndUser(
          @SuppressWarnings("unused")  LearnerGraph model,
          List<Label> question, @SuppressWarnings("unused") int valueForNoRestart,
          @SuppressWarnings("unused") List<Boolean> acceptedElements,
          @SuppressWarnings("unused") PairScore pairBeingMerged,
          @SuppressWarnings("unused")  final Object [] moreOptions)
      {
        Pair<Integer,String> oracleAnswer = new Pair<Integer,String>(expected.paths.tracePathPrefixClosed(question),null);
        return oracleAnswer;        
      }
    };
    config.setDebugMode(false);
    //l.setPairsMergedPerHypothesis(0);
    //l.setGeneralisationThreshold(1);
    //l.setCertaintyThreshold(5);
    testConfig.setLearnerIdMode(IDMode.POSITIVE_NEGATIVE);
    LearnerGraph learntStructureA = new LearnerGraph(l.learnMachine(buildSet(plus,testConfig,getLabelConverter()), buildSet(minus,testConfig,getLabelConverter())),expected.config);
    // Now do the same with ptasets instead of real sets
    PTASequenceSet plusPTA = new PTASequenceSet();plusPTA.addAll(buildSet(plus,testConfig,getLabelConverter()));PTASequenceSet minusPTA = new PTASequenceSet();minusPTA.addAll(buildSet(minus,testConfig,getLabelConverter()));
    LearnerGraph learntStructureB = new LearnerGraph(l.learnMachine(plusPTA, minusPTA),expected.config);
    Assert.assertNull(WMethod.checkM(learntStructureA, learntStructureB));
    LearnerGraph learntMachineNoRejects = new LearnerGraph(expected.config);
    AbstractPathRoutines.removeRejectStates(learntStructureA,learntMachineNoRejects);
    /*
    if (null != WMethod.checkM(learntMachineNoRejects, expected))

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Examples of statechum.analysis.learning.Learner

    for(String [] path:plus)
      assert AbstractOracle.USER_ACCEPTED == expected.paths.tracePathPrefixClosed(AbstractLearnerGraph.buildList(Arrays.asList(path),config,getLabelConverter()));
    for(String [] path:minus)
      assert AbstractOracle.USER_ACCEPTED != expected.paths.tracePathPrefixClosed(AbstractLearnerGraph.buildList(Arrays.asList(path),config,getLabelConverter()));
    // Visualiser.getVisualiser()
    Learner l = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,testConfig,null,null))
    {
      @Override
      public LearnerGraph MergeAndDeterminize(LearnerGraph original, StatePair pair) 
      {
        // Check that compatibility score computation gives the same response as if we did merge and computed a difference between the number of states.
        ScoreMode origScore = original.config.getLearnerScoreMode();original.config.setLearnerScoreMode(ScoreMode.COMPATIBILITY);
        long compatibilityScore = original.pairscores.computePairCompatibilityScore(pair);
        original.config.setLearnerScoreMode(origScore);
        LearnerGraph outcome = super.MergeAndDeterminize(original, pair);
        Assert.assertEquals(compatibilityScore+1,original.getStateNumber()-outcome.getStateNumber());
        return outcome;
      }


      @Override
      public Pair<Integer,String> CheckWithEndUser(
          @SuppressWarnings("unused")  LearnerGraph model,
          List<Label> question, @SuppressWarnings("unused") int valueForNoRestart,
          @SuppressWarnings("unused") List<Boolean> acceptedElements,
          @SuppressWarnings("unused") PairScore pairBeingMerged,
          @SuppressWarnings("unused")  final Object [] moreOptions)
      {
        Pair<Integer,String> oracleAnswer = new Pair<Integer,String>(expected.paths.tracePathPrefixClosed(question),null);
        return oracleAnswer;        
      }
      
    };
    config.setDebugMode(false);
    //l.setPairsMergedPerHypothesis(0);
    //l.setGeneralisationThreshold(1);
    //l.setCertaintyThreshold(5);
    testConfig.setLearnerIdMode(IDMode.POSITIVE_NEGATIVE);
    LearnerGraph learntStructureA = new LearnerGraph(l.learnMachine(buildSet(plus,testConfig,getLabelConverter()), buildSet(minus,testConfig,getLabelConverter())),expected.config);
    // Now do the same with ptasets instead of real sets
    PTASequenceSet plusPTA = new PTASequenceSet();plusPTA.addAll(buildSet(plus,testConfig,getLabelConverter()));PTASequenceSet minusPTA = new PTASequenceSet();minusPTA.addAll(buildSet(minus,testConfig,getLabelConverter()));
    LearnerGraph learntStructureB = new LearnerGraph(l.learnMachine(plusPTA, minusPTA),expected.config);
    Assert.assertNull(WMethod.checkM(learntStructureA, learntStructureB));
    LearnerGraph learntMachineNoRejects = new LearnerGraph(expected.config);
    AbstractPathRoutines.removeRejectStates(learntStructureA,learntMachineNoRejects);
    Assert.assertNull(WMethod.checkM(learntMachineNoRejects, expected));
  }

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Examples of statechum.analysis.learning.Learner

    { 
      initial.plus.addAll(evalData.labelDetails.getSPlus());initial.minus.addAll(evalData.labelDetails.getSMinus());
    }
    simulator.setNextElement(nextElement);


    Learner learner2 = null;


    if (logFileName.contains(Configuration.LEARNER.LEARNER_BLUEFRINGE_DEC2007.name()))
    {// have to patch the learner.
      
      learner2 = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,evalData.config,null,null))

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Examples of statechum.analysis.learning.Learner

    for(String [] path:plus)
      assert AbstractOracle.USER_ACCEPTED == expected.paths.tracePathPrefixClosed(AbstractLearnerGraph.buildList(Arrays.asList(path),config));
    for(String [] path:minus)
      assert AbstractOracle.USER_ACCEPTED != expected.paths.tracePathPrefixClosed(AbstractLearnerGraph.buildList(Arrays.asList(path),config));
    // Visualiser.getVisualiser()
    Learner l = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,testConfig,null,null))
    {
      @Override
      public Pair<Integer,String> CheckWithEndUser(
          @SuppressWarnings("unused")  LearnerGraph model,
          List<Label> question, @SuppressWarnings("unused") int valueForNoRestart,
          @SuppressWarnings("unused") List<Boolean> acceptedElements,
          @SuppressWarnings("unused") PairScore pairBeingMerged,
          @SuppressWarnings("unused")  final Object [] moreOptions)
      {
        return new Pair<Integer,String>(expected.paths.tracePathPrefixClosed(question),null);
      }
    };
    config.setDebugMode(false);
    //l.setPairsMergedPerHypothesis(0);
    //l.setGeneralisationThreshold(1);
    //l.setCertaintyThreshold(5);
    testConfig.setLearnerIdMode(IDMode.POSITIVE_NEGATIVE);
    LearnerGraph learntStructureA = new LearnerGraph(l.learnMachine(buildSet(plus,config), buildSet(minus,config)),expected.config);
    // Now do the same with ptasets instead of real sets
    PTASequenceSet plusPTA = new PTASequenceSet();plusPTA.addAll(buildSet(plus,config));PTASequenceSet minusPTA = new PTASequenceSet();minusPTA.addAll(buildSet(minus,config));
    LearnerGraph learntStructureB = new LearnerGraph(l.learnMachine(plusPTA, minusPTA),expected.config);
    Assert.assertNull(WMethod.checkM(learntStructureA, learntStructureB));
    LearnerGraph learntMachineNoRejects = new LearnerGraph(expected.config);
    AbstractPathRoutines.removeRejectStates(learntStructureA,learntMachineNoRejects);
    Assert.assertNull(WMethod.checkM(learntMachineNoRejects, expected));
  }

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Examples of statechum.analysis.learning.observers.Learner

  public static void main(String[] args) 
  {
    QSMTool tool = new QSMTool();tool.loadConfig(args[0]);
    if (tool.showLTL)
    {
      Learner l = new RPNIUniversalLearner(null,tool.learnerInitConfiguration);
      LTL_to_ba ba = new LTL_to_ba(tool.learnerInitConfiguration.config);
      if (ba.ltlToBA(tool.learnerInitConfiguration.ifthenSequences, l.init(tool.sPlus, tool.sMinus),true,
          GlobalConfiguration.getConfiguration().getProperty(GlobalConfiguration.G_PROPERTIES.LTL2BA)))
      {
        try 
        {
          Visualiser.updateFrame(PathRoutines.convertPairAssociationsToTransitions(Transform.ltlToIfThenAutomaton(ba.getLTLgraph().pathroutines.buildDeterministicGraph()), tool.learnerInitConfiguration.config), null);

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