1 files changed, 50 insertions, 71 deletions

diff --git a/Solvers/VIATRA-Solver/hu.bme.mit.inf.dslreasoner.viatrasolver.reasoner/src/hu/bme/mit/inf/dslreasoner/viatrasolver/reasoner/dse/HillClimbingOnRealisticMetricStrategyForModelGeneration.java b/Solvers/VIATRA-Solver/hu.bme.mit.inf.dslreasoner.viatrasolver.reasoner/src/hu/bme/mit/inf/dslreasoner/viatrasolver/reasoner/dse/HillClimbingOnRealisticMetricStrategyForModelGeneration.java
index 6c13e760..9409ac48 100644
--- a/Solvers/VIATRA-Solver/hu.bme.mit.inf.dslreasoner.viatrasolver.reasoner/src/hu/bme/mit/inf/dslreasoner/viatrasolver/reasoner/dse/HillClimbingOnRealisticMetricStrategyForModelGeneration.java
+++ b/Solvers/VIATRA-Solver/hu.bme.mit.inf.dslreasoner.viatrasolver.reasoner/src/hu/bme/mit/inf/dslreasoner/viatrasolver/reasoner/dse/HillClimbingOnRealisticMetricStrategyForModelGeneration.java
@@ -25,7 +25,6 @@ import org.eclipse.viatra.query.runtime.api.ViatraQueryEngine;
 import org.eclipse.viatra.query.runtime.api.ViatraQueryMatcher;
 
 import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.app.MetricDistanceGroup;
-import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.app.PartialInterpretationMetric;
 import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.app.PartialInterpretationMetricDistance;
 import hu.bme.mit.inf.dslreasoner.logic.model.builder.DocumentationLevel;
 import hu.bme.mit.inf.dslreasoner.logic.model.builder.LogicReasoner;
@@ -59,10 +58,14 @@ public class HillClimbingOnRealisticMetricStrategyForModelGeneration implements
                 private volatile boolean isInterrupted = false;
                 private ModelResult modelResultByInternalSolver = null;
                 private Random random = new Random();
+                
+                // matchers for detecting the number of violations
                 private Collection<ViatraQueryMatcher<? extends IPatternMatch>> mustMatchers;
                 private Collection<ViatraQueryMatcher<? extends IPatternMatch>> mayMatchers;
+                // Encode the used activations of a particular state
                 private Map<Object, List<Object>> stateAndActivations;
                 private Map<TrajectoryWithFitness, Double> trajectoryFit; 
+                
                 // Statistics
                 private int numberOfStatecoderFail = 0;
                 private int numberOfPrintedModel = 0;
@@ -113,16 +116,14 @@ public class HillClimbingOnRealisticMetricStrategyForModelGeneration implements
                         this.solutionStoreWithCopy = new SolutionStoreWithCopy();
                         this.solutionStoreWithDiversityDescriptor = new SolutionStoreWithDiversityDescriptor(configuration.diversityRequirement);
 
-                        //final ObjectiveComparatorHelper objectiveComparatorHelper = context.getObjectiveComparatorHelper();
                         trajectoryFit = new HashMap<TrajectoryWithFitness, Double>();
-
                         this.comparator = new Comparator<TrajectoryWithFitness>() {
                                 @Override
                                 public int compare(TrajectoryWithFitness o1, TrajectoryWithFitness o2) {
                                         return Double.compare(trajectoryFit.get(o1), trajectoryFit.get(o2));
                                 }
                         };
-
+                        
                         trajectoiresToExplore = new PriorityQueue<TrajectoryWithFitness>(11, comparator);
                         stateAndActivations = new HashMap<Object, List<Object>>();
                         metricDistance = new PartialInterpretationMetricDistance();
@@ -140,7 +141,6 @@ public class HillClimbingOnRealisticMetricStrategyForModelGeneration implements
                         }
                         
                         final Fitness firstFittness = context.calculateFitness();
-                        //checkForSolution(firstFittness);
                         
                         final ObjectiveComparatorHelper objectiveComparatorHelper = context.getObjectiveComparatorHelper();
                         final Object[] firstTrajectory = context.getTrajectory().toArray(new Object[0]);
@@ -152,7 +152,8 @@ public class HillClimbingOnRealisticMetricStrategyForModelGeneration implements
                         //if(configuration)
                         visualiseCurrentState();
                         
-                        //create matcher
+                        // the two is the True and False node generated at the beginning of the generation
+                        int targetSize = configuration.typeScopes.maxNewElements + 2;
                         int count = 0;
                         mainLoop: while (!isInterrupted && !configuration.progressMonitor.isCancelled()) {
 
@@ -181,40 +182,38 @@ public class HillClimbingOnRealisticMetricStrategyForModelGeneration implements
                                 Map<Object, Double> valueMap = new HashMap<Object,Double>();
                                 
                                 //init epsilon and draw
-                                double epsilon = 0;
-                                double draw = 1;
                                 MetricDistanceGroup heuristics =  metricDistance.calculateMetricDistanceKS(model);
 
                                 if(!stateAndActivations.containsKey(context.getCurrentStateId())) {
                                         stateAndActivations.put(context.getCurrentStateId(), new ArrayList<Object>());
                                 }
                                 
-                                //Output intermediate model
-                                if(model.getNewElements().size() > 0) {
-                                        epsilon = 1.0/count;
-                                        draw = Math.random();
-                                        count++;
-                                        // cut off the trajectory for bad graph
-                                        //System.out.println("KS");
-                                        System.out.println("NA distance: " + heuristics.getNADistance());       
-                                        System.out.println("MPC distance: " + heuristics.getMPCDistance());                             
-                                        System.out.println("Out degree distance:" + heuristics.getOutDegreeDistance()); 
-                                        System.out.println("Exit :" + heuristics.getNodeTypePercentage("Exit"));        
+                                // calculate values for epsilon greedy
+                                double epsilon = 1.0/count;
+                                double draw = Math.random();
+                                count++;
+                                
+                                // output statistics
+                                //System.out.println("KS");
+                                System.out.println("NA distance: " + heuristics.getNADistance());       
+                                System.out.println("MPC distance: " + heuristics.getMPCDistance());                             
+                                System.out.println("Out degree distance:" + heuristics.getOutDegreeDistance()); 
+                                System.out.println("NodeType :" + heuristics.getNodeTypeDistance());    
+                                System.out.println("Transition :" + heuristics.getNodeTypePercentage("Transition"));    
+                                System.out.println("FinalState :" + heuristics.getNodeTypePercentage("FinalState"));    
 
 //                                      MetricDistanceGroup lsHeuristic = metricDistance.calculateMetricDistance(model);
 //                                      System.out.println("LS");
 //                                      System.out.println("NA distance: " + lsHeuristic.getNADistance());      
 //                                      System.out.println("MPC distance: " + lsHeuristic.getMPCDistance());                            
 //                                      System.out.println("Out degree distance:" + lsHeuristic.getOutDegreeDistance());        
-                                        
-                                        //check for next value when doing greedy move
-                                        
-                                        if(activationIds.size() > 50) {
-                                                activationIds = activationIds.subList(0, 50);
-                                        }
-                                        
-                                        valueMap = sortWithWeight(activationIds, model.getNewElements().size());
+                                
+                                //TODO: the number of activations to be checked should be configurasble
+                                if(activationIds.size() > 50) {
+                                        activationIds = activationIds.subList(0, 50);
                                 }
+                                        
+                                valueMap = sortWithWeight(activationIds, model.getNewElements().size());
                                 lastState = context.getCurrentStateId();
                                 while (!isInterrupted && !configuration.progressMonitor.isCancelled() && activationIds.size() > 0) {
                                         final Object nextActivation = drawWithEpsilonProbabilty(activationIds, valueMap, epsilon, draw);
@@ -224,62 +223,44 @@ public class HillClimbingOnRealisticMetricStrategyForModelGeneration implements
                                         context.executeAcitvationId(nextActivation);
                                         visualiseCurrentState();
                                         
-                                        //calculate the metrics for each state
-//                                      logCurrentStateMetric();
-                                        
                                         boolean consistencyCheckResult = checkConsistency(currentTrajectoryWithFittness);
                                         if(consistencyCheckResult == true) { continue mainLoop; }
-                                        boolean shouldFinish = model.getNewElements().size() >= configuration.typeScopes.maxNewElements + 2;
                                         
-        /*                              if (context.isCurrentStateAlreadyTraversed()) {
-//                                              logger.info("The new state is already visited.");
+                                        int currentSize = model.getNewElements().size();
+                                        int targetDiff = targetSize - currentSize;
+                                        boolean shouldFinish = targetDiff <= 0;
+                                        
+                                        // does not allow must violations
+//                                      if((getNumberOfViolations(mustMatchers) > 0|| getNumberOfViolations(mayMatchers) > targetDiff) && !shouldFinish) {
 //                                              context.backtrack();
-//                                      } else if (!context.checkGlobalConstraints()) {
-                                                logger.debug("Global contraint is not satisifed.");
-                                                context.backtrack();
-                                        } else*/// {
-                                        if(getNumberOfViolations(mustMatchers) > 0 && !shouldFinish) {
-                                                context.backtrack();
-                                        }else if(model.getNewElements().size() > 90 && heuristics.getNADistance() + heuristics.getMPCDistance() + heuristics.getOutDegreeDistance() > 5.3) {
-                                                context.backtrack();
-                                        }else if(model.getNewElements().size() > 70 && heuristics.getNADistance() + heuristics.getMPCDistance() + heuristics.getOutDegreeDistance() > 5.45) {
-                                                context.backtrack();
-                                        } else if(model.getNewElements().size() > 50 && heuristics.getNADistance() + heuristics.getMPCDistance() + heuristics.getOutDegreeDistance() > 5.60) {
-                                                context.backtrack();
-                                        } else if(model.getNewElements().size() > 30 && heuristics.getNADistance() + heuristics.getMPCDistance() + heuristics.getOutDegreeDistance() > 5.70) {
-                                                context.backtrack();
-                                        }else {
+//                                      }else {
                                                 final Fitness nextFitness = context.calculateFitness();
                                                 
                                                 // the only hard objectives are the size
-                                                
                                                 if(shouldFinish) {
                                                         System.out.println("Solution Found!!");
-                                                        System.out.println("# violations: " + (getNumberOfViolations(mustMatchers) + getNumberOfViolations(mayMatchers)));
+                                                        System.out.println("# violations: " + (getNumberOfViolations(mustMatchers)));
                                                         nextFitness.setSatisifiesHardObjectives(true);
                                                 }
-                                                                                        
                                                 checkForSolution(nextFitness);
-                                                
-                                                
-                                                
+                                
                                                 if (context.getDepth() > configuration.searchSpaceConstraints.maxDepth) {
                                                         logger.debug("Reached max depth.");
                                                         context.backtrack();
                                                         continue;
                                                 }
-        
                                                 
+                                                //Record value for current trajectory
                                                 TrajectoryWithFitness nextTrajectoryWithFittness = new TrajectoryWithFitness(
                                                                 context.getTrajectory().toArray(), nextFitness);
-                                                int step = nextTrajectoryWithFittness.trajectory.length;
-                                                int violation = getNumberOfViolations(mustMatchers) + getNumberOfViolations(mayMatchers);
-                                                metricDistance.getLinearModel().feedData(context.getCurrentStateId(), metricDistance.calculateFeature(step, violation), calculateCurrentStateValue(step, violation), lastState);
-                                                double value = calculateCurrentStateValue(step, violation);
-                                                
+                                                int nodeSize = ((PartialInterpretation) context.getModel()).getNewElements().size();
+                                                int violation = getNumberOfViolations(mayMatchers);
+                                                metricDistance.getLinearModel().feedData(context.getCurrentStateId(), metricDistance.calculateFeature(nodeSize, violation), calculateCurrentStateValue(nodeSize, violation), lastState);
+                                                double value = calculateCurrentStateValue(nodeSize, violation);
                                                 trajectoryFit.put(nextTrajectoryWithFittness, value);
                                                 trajectoiresToExplore.add(nextTrajectoryWithFittness);
                                                 
+                                                //Currently, just go to the next state without considering the value of trajectory
                                                 int compare = objectiveComparatorHelper.compare(currentTrajectoryWithFittness.fitness,
                                                                 nextTrajectoryWithFittness.fitness);
                                                 if (compare < 0) {
@@ -301,10 +282,8 @@ public class HillClimbingOnRealisticMetricStrategyForModelGeneration implements
                                 trajectoiresToExplore.remove(currentTrajectoryWithFittness);
                                 currentTrajectoryWithFittness = null;
                                 context.backtrack();
-                        }
-//                      PartialInterpretation model = (PartialInterpretation) context.getModel();
-//                      PartialInterpretationMetric.calculateMetric(model, "debug/metric/output", context.getCurrentStateId().toString(), count);
-//                      count++;
+                        //}
+                        
                         logger.info("Interrupted.");
                 }
 
@@ -315,7 +294,8 @@ public class HillClimbingOnRealisticMetricStrategyForModelGeneration implements
                  */
                 private Map<Object, Double> sortWithWeight(List<Object> activationIds, int factor){
                         Map<Object, Double> valueMap = new HashMap<Object, Double>();
-                        // do hill climbing
+                        
+                        // check for next states
                         for(Object id : activationIds) {
                                 context.executeAcitvationId(id);
                                 int violation = getNumberOfViolations(mayMatchers);
@@ -323,6 +303,7 @@ public class HillClimbingOnRealisticMetricStrategyForModelGeneration implements
                                 context.backtrack();
                         }
                         
+                        //remove all the elements having large distance
                         activationIds.removeIf(li -> valueMap.get(li) >= 10000);
                         Collections.sort(activationIds, Comparator.comparing(li -> valueMap.get(li)));
                         return valueMap;
@@ -346,12 +327,10 @@ public class HillClimbingOnRealisticMetricStrategyForModelGeneration implements
                 private double calculateCurrentStateValue(int factor, int violation) {
                         PartialInterpretation model = (PartialInterpretation) context.getModel();
                         MetricDistanceGroup g = metricDistance.calculateMetricDistanceKS(model);
-                        if(g.getNodeTypePercentage("Exit") > 0.0) {
-                                return 10000;
-                        }
-                        double consistenceWeights = 1- 1.0/(1+violation);
-                                                
-                        return( 5.0 *(g.getNADistance() + g.getMPCDistance() + g.getOutDegreeDistance()) + consistenceWeights);
+
+                        double consistenceWeights = 5 * factor / (configuration.typeScopes.maxNewElements + 2) * (1- 1.0/(1+violation));
+                        
+                        return(100.0 *(g.getNodeTypeDistance()) + 5*(g.getNADistance() + g.getMPCDistance() +g.getOutDegreeDistance()) + consistenceWeights);
                 }
                 
                 private int getNumberOfViolations(Collection<ViatraQueryMatcher<? extends IPatternMatch>> matchers) {