Merge branch 'menu_games' of https://srv-i2.informatik.rwth-aachen.de/scm/git/storm into mergeMenuGamesWithRationalFunction

src/storm/abstraction/MenuGameRefiner.cpp

@@ -54,7 +54,7 @@ namespace storm {
         }
         
         template<storm::dd::DdType Type, typename ValueType>
-        MenuGameRefiner<Type, ValueType>::MenuGameRefiner(MenuGameAbstractor<Type, ValueType>& abstractor, std::unique_ptr<storm::solver::SmtSolver>&& smtSolver) : abstractor(abstractor), useInterpolation(storm::settings::getModule<storm::settings::modules::AbstractionSettings>().isUseInterpolationSet()), splitAll(storm::settings::getModule<storm::settings::modules::AbstractionSettings>().isSplitAllSet()), splitPredicates(storm::settings::getModule<storm::settings::modules::AbstractionSettings>().isSplitPredicatesSet()), splitGuards(storm::settings::getModule<storm::settings::modules::AbstractionSettings>().isSplitGuardsSet()), splitInitialGuards(storm::settings::getModule<storm::settings::modules::AbstractionSettings>().isSplitInitialGuardsSet()), pivotSelectionHeuristic(storm::settings::getModule<storm::settings::modules::AbstractionSettings>().getPivotSelectionHeuristic()), splitter(), equivalenceChecker(std::move(smtSolver)) {
+        MenuGameRefiner<Type, ValueType>::MenuGameRefiner(MenuGameAbstractor<Type, ValueType>& abstractor, std::unique_ptr<storm::solver::SmtSolver>&& smtSolver) : abstractor(abstractor), useInterpolation(storm::settings::getModule<storm::settings::modules::AbstractionSettings>().isUseInterpolationSet()), splitAll(storm::settings::getModule<storm::settings::modules::AbstractionSettings>().isSplitAllSet()), splitPredicates(storm::settings::getModule<storm::settings::modules::AbstractionSettings>().isSplitPredicatesSet()), splitGuards(storm::settings::getModule<storm::settings::modules::AbstractionSettings>().isSplitGuardsSet()), splitInitialGuards(storm::settings::getModule<storm::settings::modules::AbstractionSettings>().isSplitInitialGuardsSet()), addedAllGuardsFlag(false), pivotSelectionHeuristic(storm::settings::getModule<storm::settings::modules::AbstractionSettings>().getPivotSelectionHeuristic()), splitter(), equivalenceChecker(std::move(smtSolver)) {
             
             if (storm::settings::getModule<storm::settings::modules::AbstractionSettings>().isAddAllGuardsSet()) {
                 std::vector<storm::expressions::Expression> guards;
@@ -64,6 +64,8 @@ namespace storm {
                     guards.push_back(this->abstractor.get().getGuard(index));
                 }
                 performRefinement(createGlobalRefinement(preprocessPredicates(guards, RefinementPredicates::Source::InitialGuard)));
+                
+                addedAllGuardsFlag = true;
             }
         }
         
@@ -72,8 +74,6 @@ namespace storm {
             performRefinement(createGlobalRefinement(predicates));
         }
         
-//        static int cnt = 0;
-        
         template<storm::dd::DdType Type, typename ValueType>
         MostProbablePathsResult<Type, ValueType> getMostProbablePathSpanningTree(storm::abstraction::MenuGame<Type, ValueType> const& game, storm::dd::Bdd<Type> const& transitionFilter) {
             storm::dd::Add<Type, ValueType> maxProbabilities = game.getInitialStates().template toAdd<ValueType>();
@@ -589,15 +589,6 @@ namespace storm {
             // Now that we have the pivot state candidates, we need to pick one.
             PivotStateResult<Type, ValueType> pivotStateResult = pickPivotState<Type, ValueType>(pivotSelectionHeuristic, game, pivotStateCandidatesResult, qualitativeResult, boost::none);
             
-//            pivotStateResult.pivotState.template toAdd<ValueType>().exportToDot("pivot__" + std::to_string(cnt) + ".dot");
-//            (pivotStateResult.pivotState && minPlayer1Strategy).template toAdd<ValueType>().exportToDot("pivotmin_pl1__" + std::to_string(cnt) + ".dot");
-//            (pivotStateResult.pivotState && minPlayer1Strategy && minPlayer2Strategy).template toAdd<ValueType>().exportToDot("pivotmin_pl1pl2__" + std::to_string(cnt) + ".dot");
-//            ((pivotStateResult.pivotState && minPlayer1Strategy && minPlayer2Strategy).template toAdd<ValueType>() * game.getExtendedTransitionMatrix()).exportToDot("pivotmin_succ__" + std::to_string(cnt) + ".dot");
-//            (pivotStateResult.pivotState && maxPlayer1Strategy).template toAdd<ValueType>().exportToDot("pivotmax_pl1__" + std::to_string(cnt) + ".dot");
-//            (pivotStateResult.pivotState && maxPlayer1Strategy && maxPlayer2Strategy).template toAdd<ValueType>().exportToDot("pivotmax_pl1pl2__" + std::to_string(cnt) + ".dot");
-//            ((pivotStateResult.pivotState && maxPlayer1Strategy && maxPlayer2Strategy).template toAdd<ValueType>() * game.getExtendedTransitionMatrix()).exportToDot("pivotmax_succ__" + std::to_string(cnt) + ".dot");
-//            ++cnt;
-            
             boost::optional<RefinementPredicates> predicates;
             if (useInterpolation) {
                 predicates = derivePredicatesFromInterpolation(game, pivotStateResult, minPlayer1Strategy, minPlayer2Strategy, maxPlayer1Strategy, maxPlayer2Strategy);
@@ -716,6 +707,11 @@ namespace storm {
             }
         }
         
+        template<storm::dd::DdType Type, typename ValueType>
+        bool MenuGameRefiner<Type, ValueType>::addedAllGuards() const {
+            return addedAllGuardsFlag;
+        }
+        
         template class MenuGameRefiner<storm::dd::DdType::CUDD, double>;
         template class MenuGameRefiner<storm::dd::DdType::Sylvan, double>;
         

src/storm/abstraction/MenuGameRefiner.h

@@ -94,6 +94,11 @@ namespace storm {
              */
             bool refine(storm::abstraction::MenuGame<Type, ValueType> const& game, storm::dd::Bdd<Type> const& transitionMatrixBdd, QuantitativeResultMinMax<Type, ValueType> const& quantitativeResult) const;
             
+            /*!
+             * Retrieves whether all guards were added.
+             */
+            bool addedAllGuards() const;
+            
         private:
             RefinementPredicates derivePredicatesFromDifferingChoices(storm::dd::Bdd<Type> const& pivotState, storm::dd::Bdd<Type> const& player1Choice, storm::dd::Bdd<Type> const& lowerChoice, storm::dd::Bdd<Type> const& upperChoice) const;
             RefinementPredicates derivePredicatesFromPivotState(storm::abstraction::MenuGame<Type, ValueType> const& game, storm::dd::Bdd<Type> const& pivotState, storm::dd::Bdd<Type> const& minPlayer1Strategy, storm::dd::Bdd<Type> const& minPlayer2Strategy, storm::dd::Bdd<Type> const& maxPlayer1Strategy, storm::dd::Bdd<Type> const& maxPlayer2Strategy) const;
@@ -130,6 +135,9 @@ namespace storm {
             
             /// A flag indicating whether the initially added guards shall be split before using them for refinement.
             bool splitInitialGuards;
+            
+            /// A flag indicating whether all guards have been used to refine the abstraction.
+            bool addedAllGuardsFlag;
 
             /// The heuristic to use for pivot block selection.
             storm::settings::modules::AbstractionSettings::PivotSelectionHeuristic pivotSelectionHeuristic;

src/storm/modelchecker/abstraction/GameBasedMdpModelChecker.cpp

@@ -41,7 +41,7 @@ namespace storm {
         using storm::abstraction::QuantitativeResultMinMax;
         
         template<storm::dd::DdType Type, typename ModelType>
-        GameBasedMdpModelChecker<Type, ModelType>::GameBasedMdpModelChecker(storm::storage::SymbolicModelDescription const& model, std::shared_ptr<storm::utility::solver::SmtSolverFactory> const& smtSolverFactory) : smtSolverFactory(smtSolverFactory), comparator(storm::settings::getModule<storm::settings::modules::AbstractionSettings>().getPrecision()) {
+        GameBasedMdpModelChecker<Type, ModelType>::GameBasedMdpModelChecker(storm::storage::SymbolicModelDescription const& model, std::shared_ptr<storm::utility::solver::SmtSolverFactory> const& smtSolverFactory) : smtSolverFactory(smtSolverFactory), comparator(storm::settings::getModule<storm::settings::modules::AbstractionSettings>().getPrecision()), reuseQualitativeResults(false) {
             STORM_LOG_THROW(model.isPrismProgram(), storm::exceptions::NotSupportedException, "Currently only PRISM models are supported by the game-based model checker.");
             storm::prism::Program const& originalProgram = model.asPrismProgram();
             STORM_LOG_THROW(originalProgram.getModelType() == storm::prism::Program::ModelType::DTMC || originalProgram.getModelType() == storm::prism::Program::ModelType::MDP, storm::exceptions::NotSupportedException, "Currently only DTMCs/MDPs are supported by the game-based model checker.");
@@ -53,6 +53,8 @@ namespace storm {
             } else {
                 preprocessedModel = originalProgram;
             }
+            
+            reuseQualitativeResults = storm::settings::getModule<storm::settings::modules::AbstractionSettings>().isReuseQualitativeResultsSet();
         }
 
         template<storm::dd::DdType Type, typename ModelType>
@@ -289,6 +291,7 @@ namespace storm {
             refiner.refine(initialPredicates);
             
             // Enter the main-loop of abstraction refinement.
+            boost::optional<QualitativeResultMinMax<Type>> previousQualitativeResult = boost::none;
             for (uint_fast64_t iterations = 0; iterations < 10000; ++iterations) {
                 auto iterationStart = std::chrono::high_resolution_clock::now();
                 STORM_LOG_TRACE("Starting iteration " << iterations << ".");
@@ -316,11 +319,12 @@ namespace storm {
                 // (3) compute all states with probability 0/1 wrt. to the two different player 2 goals (min/max).
                 auto qualitativeStart = std::chrono::high_resolution_clock::now();
                 QualitativeResultMinMax<Type> qualitativeResult;
-                std::unique_ptr<CheckResult> result = computeProb01States(checkTask, qualitativeResult, game, player1Direction, transitionMatrixBdd, initialStates, constraintStates, targetStates);
+                std::unique_ptr<CheckResult> result = computeProb01States(checkTask, qualitativeResult, previousQualitativeResult, game, player1Direction, transitionMatrixBdd, initialStates, constraintStates, targetStates, refiner.addedAllGuards());
                 if (result) {
                     printStatistics(abstractor, game);
                     return result;
                 }
+                previousQualitativeResult = qualitativeResult;
                 auto qualitativeEnd = std::chrono::high_resolution_clock::now();
                 STORM_LOG_DEBUG("Qualitative computation completed in " << std::chrono::duration_cast<std::chrono::milliseconds>(qualitativeEnd - qualitativeStart).count() << "ms.");
                 
@@ -432,44 +436,98 @@ namespace storm {
             STORM_LOG_THROW(false, storm::exceptions::InvalidPropertyException, "Could not derive player 1 optimization direction.");
             return storm::OptimizationDirection::Maximize;
         }
-        
-        template<storm::dd::DdType Type, typename ModelType>
-        std::unique_ptr<CheckResult> GameBasedMdpModelChecker<Type, ModelType>::computeProb01States(CheckTask<storm::logic::Formula> const& checkTask, QualitativeResultMinMax<Type>& qualitativeResult, storm::abstraction::MenuGame<Type, ValueType> const& game, storm::OptimizationDirection player1Direction, storm::dd::Bdd<Type> const& transitionMatrixBdd, storm::dd::Bdd<Type> const& initialStates, storm::dd::Bdd<Type> const& constraintStates, storm::dd::Bdd<Type> const& targetStates) {
-            // TODO: use MDP functions when the directions of the players agree?
-            
-            qualitativeResult.prob0Min = computeProb01States(true, player1Direction, storm::OptimizationDirection::Minimize, game, transitionMatrixBdd, constraintStates, targetStates);
-            qualitativeResult.prob1Min = computeProb01States(false, player1Direction, storm::OptimizationDirection::Minimize, game, transitionMatrixBdd, constraintStates, targetStates);
-            std::unique_ptr<CheckResult> result = checkForResultAfterQualitativeCheck<Type, ValueType>(checkTask, storm::OptimizationDirection::Minimize, initialStates, qualitativeResult.prob0Min.getPlayer1States(), qualitativeResult.prob1Min.getPlayer1States());
-            if (!result) {
-                qualitativeResult.prob0Max = computeProb01States(true, player1Direction, storm::OptimizationDirection::Maximize, game, transitionMatrixBdd, constraintStates, targetStates);
-                
-                // As all states that have a probability 1 when player 2 minimizes will also have probability 1 when
-                // player 2 maximizes, we can take this set as the target states for thiw operation.
-                qualitativeResult.prob1Max = computeProb01States(false, player1Direction, storm::OptimizationDirection::Maximize, game, transitionMatrixBdd, constraintStates, qualitativeResult.prob1Min.player1States);
-                result = checkForResultAfterQualitativeCheck<Type, ValueType>(checkTask, storm::OptimizationDirection::Maximize, initialStates, qualitativeResult.prob0Max.getPlayer1States(), qualitativeResult.prob1Max.getPlayer1States());
+
+        template<storm::dd::DdType Type>
+        bool checkQualitativeStrategies(bool prob0, QualitativeResult<Type> const& result, storm::dd::Bdd<Type> const& targetStates) {
+            if (prob0) {
+                STORM_LOG_ASSERT(result.hasPlayer1Strategy() && (result.getPlayer1States().isZero() || !result.getPlayer1Strategy().isZero()), "Unable to proceed without strategy.");
+            } else {
+                STORM_LOG_ASSERT(result.hasPlayer1Strategy() && ((result.getPlayer1States() && !targetStates).isZero() || !result.getPlayer1Strategy().isZero()), "Unable to proceed without strategy.");
             }
+            STORM_LOG_ASSERT(result.hasPlayer2Strategy() && (result.getPlayer2States().isZero() || !result.getPlayer2Strategy().isZero()), "Unable to proceed without strategy.");
+            
+            return true;
+        }
+        
+        template<storm::dd::DdType Type>
+        bool checkQualitativeStrategies(QualitativeResultMinMax<Type> const& qualitativeResult, storm::dd::Bdd<Type> const& targetStates) {
+            bool result = true;
+            result &= checkQualitativeStrategies(true, qualitativeResult.prob0Min, targetStates);
+            result &= checkQualitativeStrategies(false, qualitativeResult.prob1Min, targetStates);
+            result &= checkQualitativeStrategies(true, qualitativeResult.prob0Max, targetStates);
+            result &= checkQualitativeStrategies(false, qualitativeResult.prob1Max, targetStates);
             return result;
         }
         
         template<storm::dd::DdType Type, typename ModelType>
-        storm::utility::graph::GameProb01Result<Type> GameBasedMdpModelChecker<Type, ModelType>::computeProb01States(bool prob0, storm::OptimizationDirection player1Direction, storm::OptimizationDirection player2Direction, storm::abstraction::MenuGame<Type, ValueType> const& game, storm::dd::Bdd<Type> const& transitionMatrixBdd, storm::dd::Bdd<Type> const& constraintStates, storm::dd::Bdd<Type> const& targetStates) {
-            auto start = std::chrono::high_resolution_clock::now();
-            storm::utility::graph::GameProb01Result<Type> result;
-            if (prob0) {
-                result = storm::utility::graph::performProb0(game, transitionMatrixBdd, constraintStates, targetStates, player1Direction, player2Direction, true, true);
+        std::unique_ptr<CheckResult> GameBasedMdpModelChecker<Type, ModelType>::computeProb01States(CheckTask<storm::logic::Formula> const& checkTask, QualitativeResultMinMax<Type>& qualitativeResult, boost::optional<QualitativeResultMinMax<Type>> const& previousQualitativeResult, storm::abstraction::MenuGame<Type, ValueType> const& game, storm::OptimizationDirection player1Direction, storm::dd::Bdd<Type> const& transitionMatrixBdd, storm::dd::Bdd<Type> const& initialStates, storm::dd::Bdd<Type> const& constraintStates, storm::dd::Bdd<Type> const& targetStates, bool addedAllGuards) {
+            
+            if (reuseQualitativeResults) {
+                // Depending on the player 1 direction, we choose a different order of operations.
+                if (player1Direction == storm::OptimizationDirection::Minimize) {
+                    // (1) min/min: compute prob0 using the game functions
+                    qualitativeResult.prob0Min = storm::utility::graph::performProb0(game, transitionMatrixBdd, constraintStates, targetStates, player1Direction, storm::OptimizationDirection::Minimize, true, true);
+                    
+                    // (2) min/min: compute prob1 using the MDP functions
+                    storm::dd::Bdd<Type> candidates = storm::utility::graph::performProbGreater0A(game, transitionMatrixBdd, constraintStates, targetStates);
+                    storm::dd::Bdd<Type> prob1MinMinMdp = storm::utility::graph::performProb1A(game, transitionMatrixBdd, constraintStates, previousQualitativeResult ? previousQualitativeResult.get().prob1Min.player1States : targetStates, candidates);
+
+                    // (3) min/min: compute prob1 using the game functions
+                    qualitativeResult.prob1Min = storm::utility::graph::performProb1(game, transitionMatrixBdd, constraintStates, targetStates, player1Direction, storm::OptimizationDirection::Minimize, true, true, boost::make_optional(prob1MinMinMdp));
+                    
+                    // (4) min/max: compute prob 0 using the game functions
+                    qualitativeResult.prob0Max = storm::utility::graph::performProb0(game, transitionMatrixBdd, constraintStates, targetStates, player1Direction, storm::OptimizationDirection::Maximize, true, true);
+                    
+                    // (5) min/max: compute prob 1 using the game functions
+                    // If the guards were previously added, we know that only previous prob1 states can now be prob 1 states again.
+                    boost::optional<storm::dd::Bdd<Type>> prob1Candidates;
+                    if (addedAllGuards && previousQualitativeResult) {
+                        prob1Candidates = previousQualitativeResult.get().prob1Max.player1States;
+                    }
+                    qualitativeResult.prob1Max = storm::utility::graph::performProb1(game, transitionMatrixBdd, constraintStates, targetStates, player1Direction, storm::OptimizationDirection::Maximize, true, true, prob1Candidates);
+                } else {
+                    // (1) max/max: compute prob0 using the game functions
+                    qualitativeResult.prob0Max = storm::utility::graph::performProb0(game, transitionMatrixBdd, constraintStates, targetStates, player1Direction, storm::OptimizationDirection::Maximize, true, true);
+                    
+                    // (2) max/max: compute prob1 using the MDP functions, reuse prob1 states of last iteration to constrain the candidate states.
+                    storm::dd::Bdd<Type> candidates = storm::utility::graph::performProbGreater0E(game, transitionMatrixBdd, constraintStates, targetStates);
+                    if (previousQualitativeResult) {
+                        candidates &= previousQualitativeResult.get().prob1Max.player1States;
+                    }
+                    storm::dd::Bdd<Type> prob1MaxMaxMdp = storm::utility::graph::performProb1E(game, transitionMatrixBdd, constraintStates, targetStates, candidates);
+                    
+                    // (3) max/max: compute prob1 using the game functions, reuse prob1 states from the MDP precomputation
+                    qualitativeResult.prob1Max = storm::utility::graph::performProb1(game, transitionMatrixBdd, constraintStates, targetStates, player1Direction, storm::OptimizationDirection::Maximize, true, true, boost::make_optional(prob1MaxMaxMdp));
+                    
+                    // (4) max/min: compute prob0 using the game functions
+                    qualitativeResult.prob0Min = storm::utility::graph::performProb0(game, transitionMatrixBdd, constraintStates, targetStates, player1Direction, storm::OptimizationDirection::Minimize, true, true);
+                    
+                    // (5) max/min: compute prob1 using the game functions, use prob1 from max/max as the candidate set
+                    qualitativeResult.prob1Min = storm::utility::graph::performProb1(game, transitionMatrixBdd, constraintStates, targetStates, player1Direction, storm::OptimizationDirection::Minimize, true, true, boost::make_optional(prob1MaxMaxMdp));
+                }
             } else {
-                result = storm::utility::graph::performProb1(game, transitionMatrixBdd, constraintStates, targetStates, player1Direction, player2Direction, true, true);
+                qualitativeResult.prob0Min = storm::utility::graph::performProb0(game, transitionMatrixBdd, constraintStates, targetStates, player1Direction, storm::OptimizationDirection::Minimize, true, true);
+                qualitativeResult.prob1Min = storm::utility::graph::performProb1(game, transitionMatrixBdd, constraintStates, targetStates, player1Direction, storm::OptimizationDirection::Minimize, true, true);
+                qualitativeResult.prob0Max = storm::utility::graph::performProb0(game, transitionMatrixBdd, constraintStates, targetStates, player1Direction, storm::OptimizationDirection::Maximize, true, true);
+                qualitativeResult.prob1Max = storm::utility::graph::performProb1(game, transitionMatrixBdd, constraintStates, targetStates, player1Direction, storm::OptimizationDirection::Maximize, true, true);
             }
             
-            if (prob0) {
-                STORM_LOG_ASSERT(result.hasPlayer1Strategy() && (result.getPlayer1States().isZero() || !result.getPlayer1Strategy().isZero()), "Unable to proceed without strategy.");
+            STORM_LOG_TRACE("Qualitative precomputation completed.");
+            STORM_LOG_TRACE("[" << player1Direction << ", " << storm::OptimizationDirection::Minimize << "]: " << qualitativeResult.prob0Min.player1States.getNonZeroCount() << " 'no', " << qualitativeResult.prob1Min.player1States.getNonZeroCount() << " 'yes'.");
+            STORM_LOG_TRACE("[" << player1Direction << ", " << storm::OptimizationDirection::Maximize << "]: " << qualitativeResult.prob0Max.player1States.getNonZeroCount() << " 'no', " << qualitativeResult.prob1Max.player1States.getNonZeroCount() << " 'yes'.");
+            
+            STORM_LOG_ASSERT(checkQualitativeStrategies(qualitativeResult, targetStates), "Qualitative strategies appear to be broken.");
+            
+            // Check for result after qualitative computations.
+            std::unique_ptr<CheckResult> result = checkForResultAfterQualitativeCheck<Type, ValueType>(checkTask, storm::OptimizationDirection::Minimize, initialStates, qualitativeResult.prob0Min.getPlayer1States(), qualitativeResult.prob1Min.getPlayer1States());
+            if (result) {
+                return result;
             } else {
-                STORM_LOG_ASSERT(result.hasPlayer1Strategy() && ((result.getPlayer1States() && !targetStates).isZero() || !result.getPlayer1Strategy().isZero()), "Unable to proceed without strategy.");
+                result = checkForResultAfterQualitativeCheck<Type, ValueType>(checkTask, storm::OptimizationDirection::Maximize, initialStates, qualitativeResult.prob0Max.getPlayer1States(), qualitativeResult.prob1Max.getPlayer1States());
+                if (result) {
+                    return result;
+                }
             }
-            STORM_LOG_ASSERT(result.hasPlayer2Strategy() && (result.getPlayer2States().isZero() || !result.getPlayer2Strategy().isZero()), "Unable to proceed without strategy.");
-
-            auto end = std::chrono::high_resolution_clock::now();
-            STORM_LOG_TRACE("Computed states with probability " << (prob0 ? "0" : "1") << " (player 1: " << player1Direction << ", player 2: " << player2Direction << "): " << result.getPlayer1States().getNonZeroCount() << " '" << (prob0 ? "no" : "yes") << "' states (completed in " << std::chrono::duration_cast<std::chrono::milliseconds>(end - start).count() << "ms).");
             
             return result;
         }

src/storm/modelchecker/abstraction/GameBasedMdpModelChecker.h

@@ -71,8 +71,7 @@ namespace storm {
              * Performs a qualitative check on the the given game to compute the (player 1) states that have probability
              * 0 or 1, respectively, to reach a target state and only visiting constraint states before.
              */
-            std::unique_ptr<CheckResult> computeProb01States(CheckTask<storm::logic::Formula> const& checkTask, QualitativeResultMinMax<Type>& qualitativeResult, storm::abstraction::MenuGame<Type, ValueType> const& game, storm::OptimizationDirection player1Direction, storm::dd::Bdd<Type> const& transitionMatrixBdd, storm::dd::Bdd<Type> const& initialStates, storm::dd::Bdd<Type> const& constraintStates, storm::dd::Bdd<Type> const& targetStates);
-            QualitativeResult<Type> computeProb01States(bool prob0, storm::OptimizationDirection player1Direction, storm::OptimizationDirection player2Direction, storm::abstraction::MenuGame<Type, ValueType> const& game, storm::dd::Bdd<Type> const& transitionMatrixBdd, storm::dd::Bdd<Type> const& constraintStates, storm::dd::Bdd<Type> const& targetStates);
+            std::unique_ptr<CheckResult> computeProb01States(CheckTask<storm::logic::Formula> const& checkTask, QualitativeResultMinMax<Type>& qualitativeResult, boost::optional<QualitativeResultMinMax<Type>> const& previousQualitativeResult, storm::abstraction::MenuGame<Type, ValueType> const& game, storm::OptimizationDirection player1Direction, storm::dd::Bdd<Type> const& transitionMatrixBdd, storm::dd::Bdd<Type> const& initialStates, storm::dd::Bdd<Type> const& constraintStates, storm::dd::Bdd<Type> const& targetStates, bool addedAllGuards);
             
             void printStatistics(storm::abstraction::MenuGameAbstractor<Type, ValueType> const& abstractor, storm::abstraction::MenuGame<Type, ValueType> const& game) const;
             
@@ -90,6 +89,9 @@ namespace storm {
             
             /// A comparator that can be used for detecting convergence.
             storm::utility::ConstantsComparator<ValueType> comparator;
+            
+            /// A flag indicating whether to reuse the qualitative results.
+            bool reuseQualitativeResults;
         };
     }
 }

src/storm/models/symbolic/StochasticTwoPlayerGame.cpp

@@ -35,7 +35,7 @@ namespace storm {
                 illegalPlayer1Mask = transitionMatrix.notZero().existsAbstract(this->getColumnVariables()).existsAbstract(this->getPlayer2Variables());
                 
                 // Correct the mask for player 2. This is necessary, because it is not yet restricted to the legal choices of player 1.
-                this->illegalMask &= illegalPlayer1Mask;
+                illegalPlayer2Mask = this->getIllegalMask() && illegalPlayer1Mask;
                 
                 // Then set the illegal mask for player 1 correctly.
                 illegalPlayer1Mask = !illegalPlayer1Mask && reachableStates;
@@ -48,8 +48,7 @@ namespace storm {
             
             template<storm::dd::DdType Type, typename ValueType>
             storm::dd::Bdd<Type> StochasticTwoPlayerGame<Type, ValueType>::getIllegalPlayer2Mask() const {
-                // For player 2, we can simply return the mask of the superclass.
-                return this->getIllegalMask();
+                return illegalPlayer2Mask;
             }
             
             template<storm::dd::DdType Type, typename ValueType>

src/storm/models/symbolic/StochasticTwoPlayerGame.h

@@ -90,10 +90,12 @@ namespace storm {
                 storm::dd::Bdd<Type> getIllegalPlayer2Mask() const;
                 
             private:
-                // A mask that characterizes all illegal player 1 choices. The mask for player 2 is given by the mask
-                // of the superclass (nondeterminstic model).
+                // A mask that characterizes all illegal player 1 choices.
                 storm::dd::Bdd<Type> illegalPlayer1Mask;
 
+                // A mask that characterizes all illegal player 2 choices.
+                storm::dd::Bdd<Type> illegalPlayer2Mask;
+
                 // The meta variables used to encode the nondeterministic choices of player 1.
                 std::set<storm::expressions::Variable> player1Variables;
                 

src/storm/settings/modules/AbstractionSettings.cpp

@@ -20,6 +20,7 @@ namespace storm {
             const std::string AbstractionSettings::precisionOptionName = "precision";
             const std::string AbstractionSettings::pivotHeuristicOptionName = "pivot-heuristic";
             const std::string AbstractionSettings::invalidBlockStrategyOptionName = "invalid-blocks";
+            const std::string AbstractionSettings::reuseQualitativeResultsOptionName = "reuse-qualitative";
 
             AbstractionSettings::AbstractionSettings() : ModuleSettings(moduleName) {
                 this->addOption(storm::settings::OptionBuilder(moduleName, addAllGuardsOptionName, true, "Sets whether all guards are added as initial predicates.").build());
@@ -29,6 +30,7 @@ namespace storm {
                 this->addOption(storm::settings::OptionBuilder(moduleName, splitAllOptionName, true, "Sets whether all predicates are split into atoms before they are added.").build());
                 this->addOption(storm::settings::OptionBuilder(moduleName, useInterpolationOptionName, true, "Sets whether interpolation is to be used to eliminate spurious pivot blocks.").build());
                 this->addOption(storm::settings::OptionBuilder(moduleName, precisionOptionName, true, "The precision used for detecting convergence.").addArgument(storm::settings::ArgumentBuilder::createDoubleArgument("value", "The precision to achieve.").setDefaultValueDouble(1e-03).addValidationFunctionDouble(storm::settings::ArgumentValidators::doubleRangeValidatorExcluding(0.0, 1.0)).build()).build());
+
                 std::vector<std::string> pivotHeuristic = {"nearest-max-dev", "most-prob-path", "max-weighted-dev"};
                 this->addOption(storm::settings::OptionBuilder(moduleName, pivotHeuristicOptionName, true, "Sets the pivot selection heuristic.")
                                 .addArgument(storm::settings::ArgumentBuilder::createStringArgument("name", "The name of an available heuristic. Available are: 'nearest-max-dev', 'most-prob-path' and 'max-weighted-dev'.").addValidationFunctionString(storm::settings::ArgumentValidators::stringInListValidator(pivotHeuristic)).setDefaultValueString("nearest-max-dev").build()).build());
@@ -36,6 +38,8 @@ namespace storm {
                 std::vector<std::string> invalidBlockStrategies = {"none", "command", "global"};
                 this->addOption(storm::settings::OptionBuilder(moduleName, invalidBlockStrategyOptionName, true, "Sets the strategy to detect invalid blocks.")
                                 .addArgument(storm::settings::ArgumentBuilder::createStringArgument("name", "The name of an available strategy. Available are: 'none', 'command' and 'global'.").addValidationFunctionString(storm::settings::ArgumentValidators::stringInListValidator(invalidBlockStrategies)).setDefaultValueString("global").build()).build());
+                
+                this->addOption(storm::settings::OptionBuilder(moduleName, reuseQualitativeResultsOptionName, true, "Sets whether to reuse qualitative results.").build());
             }
             
             bool AbstractionSettings::isAddAllGuardsSet() const {
@@ -89,6 +93,10 @@ namespace storm {
                 }
                 STORM_LOG_THROW(false, storm::exceptions::IllegalArgumentValueException, "Unknown invalid block detection strategy '" << strategyName << "'.");
             }
+            
+            bool AbstractionSettings::isReuseQualitativeResultsSet() const {
+                return this->getOption(reuseQualitativeResultsOptionName).getHasOptionBeenSet();
+            }
         }
     }
 }

src/storm/settings/modules/AbstractionSettings.h

@@ -86,6 +86,13 @@ namespace storm {
                  * @return The strategy to use
                  */
                 InvalidBlockDetectionStrategy getInvalidBlockDetectionStrategy() const;
+                
+                /*!
+                 * Retrieves whether the option to reuse the qualitative results.
+                 *
+                 * @param True iff the option was set.
+                 */
+                bool isReuseQualitativeResultsSet() const;
 
                 const static std::string moduleName;
                 
@@ -100,6 +107,7 @@ namespace storm {
                 const static std::string precisionOptionName;
                 const static std::string pivotHeuristicOptionName;
                 const static std::string invalidBlockStrategyOptionName;
+                const static std::string reuseQualitativeResultsOptionName;
             };
             
         }

src/storm/utility/dd.cpp

@@ -33,7 +33,7 @@ namespace storm {
                 } while (changed);
 
                 auto end = std::chrono::high_resolution_clock::now();
-                STORM_LOG_TRACE("Reachability computation completed in " << iteration << " iterations (" << std::chrono::duration_cast<std::chrono::milliseconds>(end - start).count() << "ms.");
+                STORM_LOG_TRACE("Reachability computation completed in " << iteration << " iterations (" << std::chrono::duration_cast<std::chrono::milliseconds>(end - start).count() << "ms).");
                 
                 return reachableStates;
             }

src/storm/utility/graph.cpp

@@ -991,12 +991,16 @@ namespace storm {
             }
             
             template <storm::dd::DdType Type, typename ValueType>
-            GameProb01Result<Type> performProb1(storm::models::symbolic::StochasticTwoPlayerGame<Type, ValueType> const& model, storm::dd::Bdd<Type> const& transitionMatrix, storm::dd::Bdd<Type> const& phiStates, storm::dd::Bdd<Type> const& psiStates, storm::OptimizationDirection const& player1Strategy, storm::OptimizationDirection const& player2Strategy, bool producePlayer1Strategy, bool producePlayer2Strategy) {
+            GameProb01Result<Type> performProb1(storm::models::symbolic::StochasticTwoPlayerGame<Type, ValueType> const& model, storm::dd::Bdd<Type> const& transitionMatrix, storm::dd::Bdd<Type> const& phiStates, storm::dd::Bdd<Type> const& psiStates, storm::OptimizationDirection const& player1Strategy, storm::OptimizationDirection const& player2Strategy, bool producePlayer1Strategy, bool producePlayer2Strategy, boost::optional<storm::dd::Bdd<Type>> const& player1Candidates) {
                 
-                // Create two sets of states. Those states for which we definitely know that their probability is 1 and
-                // those states that potentially have a probability of 1.
+                // Create the potential prob1 states of player 1.
                 storm::dd::Bdd<Type> maybePlayer1States = model.getReachableStates();
-                storm::dd::Bdd<Type> maybePlayer2States = model.getReachableStates();
+                if (player1Candidates) {
+                    maybePlayer1States &= player1Candidates.get();
+                }
+                
+                // Initialize potential prob1 states of player 2.
+                storm::dd::Bdd<Type> maybePlayer2States = model.getManager().getBddZero();
 
                 // A flag that governs whether strategies are produced in the current iteration.
                 bool produceStrategiesInIteration = false;
@@ -1523,7 +1527,7 @@ namespace storm {
             
             template GameProb01Result<storm::dd::DdType::CUDD> performProb0(storm::models::symbolic::StochasticTwoPlayerGame<storm::dd::DdType::CUDD, double> const& model, storm::dd::Bdd<storm::dd::DdType::CUDD> const& transitionMatrix, storm::dd::Bdd<storm::dd::DdType::CUDD> const& phiStates, storm::dd::Bdd<storm::dd::DdType::CUDD> const& psiStates, storm::OptimizationDirection const& player1Strategy, storm::OptimizationDirection const& player2Strategy, bool producePlayer1Strategy, bool producePlayer2Strategy);
             
-            template GameProb01Result<storm::dd::DdType::CUDD> performProb1(storm::models::symbolic::StochasticTwoPlayerGame<storm::dd::DdType::CUDD, double> const& model, storm::dd::Bdd<storm::dd::DdType::CUDD> const& transitionMatrix, storm::dd::Bdd<storm::dd::DdType::CUDD> const& phiStates, storm::dd::Bdd<storm::dd::DdType::CUDD> const& psiStates, storm::OptimizationDirection const& player1Strategy, storm::OptimizationDirection const& player2Strategy, bool producePlayer1Strategy, bool producePlayer2Strategy);
+            template GameProb01Result<storm::dd::DdType::CUDD> performProb1(storm::models::symbolic::StochasticTwoPlayerGame<storm::dd::DdType::CUDD, double> const& model, storm::dd::Bdd<storm::dd::DdType::CUDD> const& transitionMatrix, storm::dd::Bdd<storm::dd::DdType::CUDD> const& phiStates, storm::dd::Bdd<storm::dd::DdType::CUDD> const& psiStates, storm::OptimizationDirection const& player1Strategy, storm::OptimizationDirection const& player2Strategy, bool producePlayer1Strategy, bool producePlayer2Strategy, boost::optional<storm::dd::Bdd<storm::dd::DdType::CUDD>> const& player1Candidates);
 
             // Instantiations for Sylvan.
             
@@ -1555,7 +1559,7 @@ namespace storm {
 
             template GameProb01Result<storm::dd::DdType::Sylvan> performProb0(storm::models::symbolic::StochasticTwoPlayerGame<storm::dd::DdType::Sylvan> const& model, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& transitionMatrix, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& phiStates, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& psiStates, storm::OptimizationDirection const& player1Strategy, storm::OptimizationDirection const& player2Strategy, bool producePlayer1Strategy, bool producePlayer2Strategy);
 
-            template GameProb01Result<storm::dd::DdType::Sylvan> performProb1(storm::models::symbolic::StochasticTwoPlayerGame<storm::dd::DdType::Sylvan> const& model, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& transitionMatrix, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& phiStates, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& psiStates, storm::OptimizationDirection const& player1Strategy, storm::OptimizationDirection const& player2Strategy, bool producePlayer1Strategy, bool producePlayer2Strategy);
+            template GameProb01Result<storm::dd::DdType::Sylvan> performProb1(storm::models::symbolic::StochasticTwoPlayerGame<storm::dd::DdType::Sylvan> const& model, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& transitionMatrix, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& phiStates, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& psiStates, storm::OptimizationDirection const& player1Strategy, storm::OptimizationDirection const& player2Strategy, bool producePlayer1Strategy, bool producePlayer2Strategy, boost::optional<storm::dd::Bdd<storm::dd::DdType::Sylvan>> const& player1Candidates);
 
         } // namespace graph
     } // namespace utility

src/storm/utility/graph.h

@@ -589,9 +589,10 @@ namespace storm {
              * @param psiStates The BDD containing all psi states of the model.
              * @param producePlayer1Strategy A flag indicating whether the strategy of player 1 shall be produced.
              * @param producePlayer2Strategy A flag indicating whether the strategy of player 2 shall be produced.
+             * @param player1Candidates If given, this set constrains the candidates of player 1 states that are considered.
              */
             template <storm::dd::DdType Type, typename ValueType>
-            GameProb01Result<Type> performProb1(storm::models::symbolic::StochasticTwoPlayerGame<Type, ValueType> const& model, storm::dd::Bdd<Type> const& transitionMatrix, storm::dd::Bdd<Type> const& phiStates, storm::dd::Bdd<Type> const& psiStates, storm::OptimizationDirection const& player1Strategy, storm::OptimizationDirection const& player2Strategy, bool producePlayer1Strategy = false, bool producePlayer2Strategy = false);
+            GameProb01Result<Type> performProb1(storm::models::symbolic::StochasticTwoPlayerGame<Type, ValueType> const& model, storm::dd::Bdd<Type> const& transitionMatrix, storm::dd::Bdd<Type> const& phiStates, storm::dd::Bdd<Type> const& psiStates, storm::OptimizationDirection const& player1Strategy, storm::OptimizationDirection const& player2Strategy, bool producePlayer1Strategy = false, bool producePlayer2Strategy = false, boost::optional<storm::dd::Bdd<Type>> const& player1Candidates = boost::none);
             
             /*!
              * Performs a topological sort of the states of the system according to the given transitions.