18namespace modelchecker {
19template<
typename ModelType>
25template<
typename ModelType>
42 return checkTask.
getFormula().isInFragment(singleObjectiveFragment);
45template<
typename ModelType>
47 return canHandleStatic(checkTask);
50template<
typename ModelType>
54 "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model.");
56 std::unique_ptr<CheckResult> leftResultPointer = this->check(env, pathFormula.
getLeftSubformula());
57 std::unique_ptr<CheckResult> rightResultPointer = this->check(env, pathFormula.
getRightSubformula());
66template<
typename ModelType>
70 "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model.");
72 std::unique_ptr<CheckResult> subResultPointer = this->check(env, eventuallyFormula.
getSubformula());
75 return storm::modelchecker::helper::HybridMarkovAutomatonCslHelper::computeReachabilityRewards<DdType, ValueType>(
76 env, checkTask.
getOptimizationDirection(), this->getModel(), this->getModel().getTransitionMatrix(), this->getModel().getMarkovianStates(),
80template<
typename ModelType>
84 "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model.");
87 std::unique_ptr<CheckResult> subResultPointer = this->check(env, eventuallyFormula.
getSubformula());
91 boost::none, boost::none);
92 return storm::modelchecker::helper::HybridMarkovAutomatonCslHelper::computeReachabilityRewards<DdType, ValueType>(
93 env, checkTask.
getOptimizationDirection(), this->getModel(), this->getModel().getTransitionMatrix(), this->getModel().getMarkovianStates(),
97template<
typename ModelType>
101 std::unique_ptr<CheckResult> leftResultPointer = this->check(env, pathFormula.
getLeftSubformula());
104 std::unique_ptr<CheckResult> rightResultPointer = this->check(env, pathFormula.
getRightSubformula());
108 "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model.");
110 "Currently step-bounded and reward-bounded properties on MarkovAutomatons are not supported.");
111 double lowerBound = 0;
112 double upperBound = 0;
119 upperBound = storm::utility::infinity<double>();
122 return storm::modelchecker::helper::HybridMarkovAutomatonCslHelper::computeBoundedUntilProbabilities<DdType, ValueType>(
123 env, checkTask.
getOptimizationDirection(), this->getModel(), this->getModel().getTransitionMatrix(), this->getModel().getMarkovianStates(),
128template<
typename ModelType>
132 std::unique_ptr<CheckResult> subResultPointer = this->check(env, stateFormula);
135 "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model.");
138 this->getModel(), this->getModel().getTransitionMatrix(), this->getModel().getMarkovianStates(), this->getModel().getExitRateVector());
143template<
typename ModelType>
147 "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model.");
150 this->getModel(), this->getModel().getTransitionMatrix(), this->getModel().getMarkovianStates(), this->getModel().getExitRateVector());
FragmentSpecification & setNextFormulasAllowed(bool newValue)
FragmentSpecification & setRewardAccumulationAllowed(bool newValue)
FragmentSpecification & setGloballyFormulasAllowed(bool newValue)
FragmentSpecification & setCumulativeRewardFormulasAllowed(bool newValue)
FragmentSpecification & setTotalRewardFormulasAllowed(bool newValue)
FragmentSpecification & setReachabilityRewardFormulasAllowed(bool newValue)
FragmentSpecification & setLongRunAverageRewardFormulasAllowed(bool newValue)
FragmentSpecification & setLongRunAverageProbabilitiesAllowed(bool newValue)
FragmentSpecification & setRewardOperatorsAllowed(bool newValue)
FragmentSpecification & setBoundedUntilFormulasAllowed(bool newValue)
FragmentSpecification & setInstantaneousFormulasAllowed(bool newValue)
FragmentSpecification & setTimeAllowed(bool newValue)
SymbolicQualitativeCheckResult< Type > & asSymbolicQualitativeCheckResult()
bool isOptimizationDirectionSet() const
Retrieves whether an optimization direction was set.
bool isQualitativeSet() const
Retrieves whether the computation only needs to be performed qualitatively, because the values will o...
FormulaType const & getFormula() const
Retrieves the formula from this task.
storm::OptimizationDirection const & getOptimizationDirection() const
Retrieves the optimization direction (if set).
static bool canHandleStatic(CheckTask< storm::logic::Formula, ValueType > const &checkTask)
virtual std::unique_ptr< CheckResult > computeUntilProbabilities(Environment const &env, CheckTask< storm::logic::UntilFormula, ValueType > const &checkTask) override
virtual std::unique_ptr< CheckResult > computeLongRunAverageProbabilities(Environment const &env, CheckTask< storm::logic::StateFormula, ValueType > const &checkTask) override
virtual bool canHandle(CheckTask< storm::logic::Formula, ValueType > const &checkTask) const override
virtual std::unique_ptr< CheckResult > computeBoundedUntilProbabilities(Environment const &env, CheckTask< storm::logic::BoundedUntilFormula, ValueType > const &checkTask) override
virtual std::unique_ptr< CheckResult > computeReachabilityTimes(Environment const &env, CheckTask< storm::logic::EventuallyFormula, ValueType > const &checkTask) override
virtual std::unique_ptr< CheckResult > computeLongRunAverageRewards(Environment const &env, CheckTask< storm::logic::LongRunAverageRewardFormula, ValueType > const &checkTask) override
virtual std::unique_ptr< CheckResult > computeReachabilityRewards(Environment const &env, CheckTask< storm::logic::EventuallyFormula, ValueType > const &checkTask) override
HybridMarkovAutomatonCslModelChecker(ModelType const &model)
storm::dd::Bdd< Type > const & getTruthValuesVector() const
Helper class for model checking queries that depend on the long run behavior of the (nondeterministic...
std::unique_ptr< HybridQuantitativeCheckResult< DdType, ValueType > > computeLongRunAverageProbabilities(Environment const &env, storm::dd::Bdd< DdType > const &psiStates)
Computes the long run average probabilities, i.e., the fraction of the time we are in a psiState.
std::unique_ptr< HybridQuantitativeCheckResult< DdType, ValueType > > computeLongRunAverageRewards(Environment const &env, storm::models::symbolic::StandardRewardModel< DdType, ValueType > const &rewardModel)
Computes the long run average rewards, i.e., the average reward collected per time unit.
static std::unique_ptr< CheckResult > computeUntilProbabilities(Environment const &env, OptimizationDirection dir, storm::models::symbolic::NondeterministicModel< DdType, ValueType > const &model, storm::dd::Add< DdType, ValueType > const &transitionMatrix, storm::dd::Bdd< DdType > const &phiStates, storm::dd::Bdd< DdType > const &psiStates, bool qualitative)
#define STORM_LOG_THROW(cond, exception, message)
FragmentSpecification csl()
void setInformationFromCheckTaskNondeterministic(HelperType &helper, storm::modelchecker::CheckTask< FormulaType, typename ModelType::ValueType > const &checkTask, ModelType const &model)
Forwards relevant information stored in the given CheckTask to the given helper.
FilteredRewardModel< RewardModelType > createFilteredRewardModel(RewardModelType const &baseRewardModel, storm::logic::RewardAccumulation const &acc, bool isDiscreteTimeModel)