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Hybrid MA engine: (bounded) reachability probabilities

tempestpy_adaptions
Tim Quatmann 5 years ago
parent
72eb58f73d
commit
73b68836c5
4 changed files with 43 additions and 256 deletions
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  1. 37
      src/storm/modelchecker/csl/HybridMarkovAutomatonCslModelChecker.cpp
  2. 12
      src/storm/modelchecker/csl/HybridMarkovAutomatonCslModelChecker.h
  3. 223
      src/storm/modelchecker/csl/helper/HybridMarkovAutomatonCslHelper.cpp
  4. 15
      src/storm/modelchecker/csl/helper/HybridMarkovAutomatonCslHelper.h

37
src/storm/modelchecker/csl/HybridMarkovAutomatonCslModelChecker.cpp
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@ -4,6 +4,7 @@
#include "storm/modelchecker/csl/helper/SparseMarkovAutomatonCslHelper.h"
#include "storm/modelchecker/csl/helper/HybridMarkovAutomatonCslHelper.h"
#include "storm/modelchecker/prctl/helper/HybridMdpPrctlHelper.h"
#include "storm/modelchecker/results/SymbolicQualitativeCheckResult.h"
@ -26,7 +27,7 @@ namespace storm {
template <typename ModelType>
bool HybridMarkovAutomatonCslModelChecker<ModelType>::canHandleStatic(CheckTask<storm::logic::Formula, ValueType> const& checkTask) {
auto singleObjectiveFragment = storm::logic::csl().setGloballyFormulasAllowed(false).setNextFormulasAllowed(false).setRewardOperatorsAllowed(true).setReachabilityRewardFormulasAllowed(true).setTotalRewardFormulasAllowed(true).setTimeAllowed(true).setLongRunAverageProbabilitiesAllowed(true).setLongRunAverageRewardFormulasAllowed(true).setRewardAccumulationAllowed(true).setInstantaneousFormulasAllowed(false).setCumulativeRewardFormulasAllowed(false);
auto singleObjectiveFragment = storm::logic::csl().setGloballyFormulasAllowed(false).setNextFormulasAllowed(false).setRewardOperatorsAllowed(true).setReachabilityRewardFormulasAllowed(true).setTotalRewardFormulasAllowed(false).setTimeAllowed(true).setLongRunAverageProbabilitiesAllowed(false).setLongRunAverageRewardFormulasAllowed(false).setRewardAccumulationAllowed(true).setInstantaneousFormulasAllowed(false).setCumulativeRewardFormulasAllowed(false);
if (!storm::NumberTraits<ValueType>::SupportsExponential) {
singleObjectiveFragment.setBoundedUntilFormulasAllowed(false);
}
@ -38,17 +39,18 @@ namespace storm {
return canHandleStatic(checkTask);
}
/* template<typename ModelType>
template<typename ModelType>
std::unique_ptr<CheckResult> HybridMarkovAutomatonCslModelChecker<ModelType>::computeUntilProbabilities(Environment const& env, CheckTask<storm::logic::UntilFormula, ValueType> const& checkTask) {
STORM_LOG_THROW(checkTask.isOptimizationDirectionSet(), storm::exceptions::InvalidPropertyException, "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model.");
storm::logic::UntilFormula const& pathFormula = checkTask.getFormula();
std::unique_ptr<CheckResult> leftResultPointer = this->check(env, pathFormula.getLeftSubformula());
std::unique_ptr<CheckResult> rightResultPointer = this->check(env, pathFormula.getRightSubformula());
SymbolicQualitativeCheckResult<DdType> const& leftResult = leftResultPointer->asSymbolicQualitativeCheckResult<DdType>();
SymbolicQualitativeCheckResult<DdType> const& rightResult = rightResultPointer->asSymbolicQualitativeCheckResult<DdType>();
return storm::modelchecker::helper::HybridMarkovAutomatonCslHelper::computeUntilProbabilities<DdType, ValueType>(env, this->getModel(), this->getModel().getTransitionMatrix(), this->getModel().getMarkovianStates(), this->getModel().getExitRateVector(), leftResult.getTruthValuesVector(), rightResult.getTruthValuesVector(), checkTask.isQualitativeSet());
return storm::modelchecker::helper::HybridMdpPrctlHelper<DdType, ValueType>::computeUntilProbabilities(env, checkTask.getOptimizationDirection(), this->getModel(), this->getModel().getTransitionMatrix(), leftResult.getTruthValuesVector(), rightResult.getTruthValuesVector(), checkTask.isQualitativeSet());
}
*/
template<typename ModelType>
std::unique_ptr<CheckResult> HybridMarkovAutomatonCslModelChecker<ModelType>::computeReachabilityRewards(Environment const& env, storm::logic::RewardMeasureType, CheckTask<storm::logic::EventuallyFormula, ValueType> const& checkTask) {
STORM_LOG_THROW(checkTask.isOptimizationDirectionSet(), storm::exceptions::InvalidPropertyException, "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model.");
@ -59,24 +61,26 @@ namespace storm {
return storm::modelchecker::helper::HybridMarkovAutomatonCslHelper::computeReachabilityRewards<DdType, ValueType>(env, checkTask.getOptimizationDirection(), this->getModel(), this->getModel().getTransitionMatrix(), this->getModel().getMarkovianStates(), this->getModel().getExitRateVector(), rewardModel.get(), subResult.getTruthValuesVector(), checkTask.isQualitativeSet());
}
/* template<typename ModelType>
template<typename ModelType>
std::unique_ptr<CheckResult> HybridMarkovAutomatonCslModelChecker<ModelType>::computeReachabilityTimes(Environment const& env, storm::logic::RewardMeasureType, CheckTask<storm::logic::EventuallyFormula, ValueType> const& checkTask) {
STORM_LOG_THROW(checkTask.isOptimizationDirectionSet(), storm::exceptions::InvalidPropertyException, "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model.");
storm::logic::EventuallyFormula const& eventuallyFormula = checkTask.getFormula();
std::unique_ptr<CheckResult> subResultPointer = this->check(env, eventuallyFormula.getSubformula());
SymbolicQualitativeCheckResult<DdType> const& subResult = subResultPointer->asSymbolicQualitativeCheckResult<DdType>();
storm::models::symbolic::StandardRewardModel<DdType, ValueType> timeRewardModel(this->getModel().getManager().getConstant(storm::utility::one<ValueType>()), boost::none, boost::none);
return storm::modelchecker::helper::HybridMarkovAutomatonCslHelper::computeReachabilityRewards<DdType, ValueType>(env, this->getModel(), this->getModel().getTransitionMatrix(), this->getModel().getMarkovianStates(), this->getModel().getExitRateVector(), timeRewardModel, subResult.getTruthValuesVector(), checkTask.isQualitativeSet());
return storm::modelchecker::helper::HybridMarkovAutomatonCslHelper::computeReachabilityRewards<DdType, ValueType>(env, checkTask.getOptimizationDirection(), this->getModel(), this->getModel().getTransitionMatrix(), this->getModel().getMarkovianStates(), this->getModel().getExitRateVector(), timeRewardModel, subResult.getTruthValuesVector(), checkTask.isQualitativeSet());
}
template<typename ModelType>
std::unique_ptr<CheckResult> HybridMarkovAutomatonCslModelChecker<ModelType>::computeBoundedUntilProbabilities(Environment const& env, CheckTask<storm::logic::BoundedUntilFormula, ValueType> const& checkTask) {
storm::logic::BoundedUntilFormula const& pathFormula = checkTask.getFormula();
std::unique_ptr<CheckResult> leftResultPointer = this->check(env, pathFormula.getLeftSubformula());
STORM_LOG_THROW(pathFormula.getLeftSubformula().isTrueFormula(), storm::exceptions::NotImplementedException, "Only bounded properties of the form 'true U[t1, t2] phi' are currently supported.");
std::unique_ptr<CheckResult> rightResultPointer = this->check(env, pathFormula.getRightSubformula());
SymbolicQualitativeCheckResult<DdType> const& leftResult = leftResultPointer->asSymbolicQualitativeCheckResult<DdType>();
SymbolicQualitativeCheckResult<DdType> const& rightResult = rightResultPointer->asSymbolicQualitativeCheckResult<DdType>();
STORM_LOG_THROW(checkTask.isOptimizationDirectionSet(), storm::exceptions::InvalidPropertyException, "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model.");
STORM_LOG_THROW(pathFormula.getTimeBoundReference().isTimeBound(), storm::exceptions::NotImplementedException, "Currently step-bounded and reward-bounded properties on MarkovAutomatons are not supported.");
double lowerBound = 0;
double upperBound = 0;
@ -89,24 +93,9 @@ namespace storm {
upperBound = storm::utility::infinity<double>();
}
return storm::modelchecker::helper::HybridMarkovAutomatonCslHelper::computeBoundedUntilProbabilities<DdType, ValueType>(env, this->getModel(), this->getModel().getTransitionMatrix(), this->getModel().getMarkovianStates(), this->getModel().getExitRateVector(), leftResult.getTruthValuesVector(), rightResult.getTruthValuesVector(), checkTask.isQualitativeSet(), lowerBound, upperBound);
return storm::modelchecker::helper::HybridMarkovAutomatonCslHelper::computeBoundedUntilProbabilities<DdType, ValueType>(env, checkTask.getOptimizationDirection(), this->getModel(), this->getModel().getTransitionMatrix(), this->getModel().getMarkovianStates(), this->getModel().getExitRateVector(), rightResult.getTruthValuesVector(), checkTask.isQualitativeSet(), lowerBound, upperBound);
}
template<typename ModelType>
std::unique_ptr<CheckResult> HybridMarkovAutomatonCslModelChecker<ModelType>::computeLongRunAverageProbabilities(Environment const& env, CheckTask<storm::logic::StateFormula, ValueType> const& checkTask) {
storm::logic::StateFormula const& stateFormula = checkTask.getFormula();
std::unique_ptr<CheckResult> subResultPointer = this->check(env, stateFormula);
SymbolicQualitativeCheckResult<DdType> const& subResult = subResultPointer->asSymbolicQualitativeCheckResult<DdType>();
return storm::modelchecker::helper::HybridMarkovAutomatonCslHelper::computeLongRunAverageProbabilities<DdType, ValueType>(env, this->getModel(), this->getModel().getTransitionMatrix(), this->getModel().getMarkovianStates(), this->getModel().getExitRateVector(), subResult.getTruthValuesVector());
}
template<typename ModelType>
std::unique_ptr<CheckResult> HybridMarkovAutomatonCslModelChecker<ModelType>::computeLongRunAverageRewards(Environment const& env, storm::logic::RewardMeasureType rewardMeasureType, CheckTask<storm::logic::LongRunAverageRewardFormula, ValueType> const& checkTask) {
auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
return storm::modelchecker::helper::HybridMarkovAutomatonCslHelper::computeLongRunAverageRewards<DdType, ValueType>(env, this->getModel(), this->getModel().getTransitionMatrix(), this->getModel().getMarkovianStates(), this->getModel().getExitRateVector(), rewardModel.get());
}
*/
// Explicitly instantiate the model checker.
template class HybridMarkovAutomatonCslModelChecker<storm::models::symbolic::MarkovAutomaton<storm::dd::DdType::CUDD, double>>;
template class HybridMarkovAutomatonCslModelChecker<storm::models::symbolic::MarkovAutomaton<storm::dd::DdType::Sylvan, double>>;

12
src/storm/modelchecker/csl/HybridMarkovAutomatonCslModelChecker.h
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@ -23,16 +23,10 @@ namespace storm {
// The implemented methods of the AbstractModelChecker interface.
static bool canHandleStatic(CheckTask<storm::logic::Formula, ValueType> const& checkTask);
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> computeNextProbabilities(Environment const& env, CheckTask<storm::logic::NextFormula, ValueType> const& checkTask) override;
virtual std::unique_ptr<CheckResult> computeBoundedUntilProbabilities(Environment const& env, CheckTask<storm::logic::BoundedUntilFormula, ValueType> const& checkTask) override;
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 std::unique_ptr<CheckResult> computeLongRunAverageRewards(Environment const& env, storm::logic::RewardMeasureType rewardMeasureType, CheckTask<storm::logic::LongRunAverageRewardFormula, ValueType> const& checkTask) override;
virtual std::unique_ptr<CheckResult> computeInstantaneousRewards(Environment const& env, storm::logic::RewardMeasureType rewardMeasureType, CheckTask<storm::logic::InstantaneousRewardFormula, ValueType> const& checkTask) override;
virtual std::unique_ptr<CheckResult> computeCumulativeRewards(Environment const& env, storm::logic::RewardMeasureType rewardMeasureType, CheckTask<storm::logic::CumulativeRewardFormula, ValueType> const& checkTask) override;
*/ virtual std::unique_ptr<CheckResult> computeReachabilityRewards(Environment const& env, storm::logic::RewardMeasureType rewardMeasureType, CheckTask<storm::logic::EventuallyFormula, ValueType> const& checkTask) override;
//virtual std::unique_ptr<CheckResult> computeReachabilityTimes(Environment const& env, storm::logic::RewardMeasureType rewardMeasureType, CheckTask<storm::logic::EventuallyFormula, ValueType> const& checkTask) override;
virtual std::unique_ptr<CheckResult> computeReachabilityRewards(Environment const& env, storm::logic::RewardMeasureType rewardMeasureType, CheckTask<storm::logic::EventuallyFormula, ValueType> const& checkTask) override;
virtual std::unique_ptr<CheckResult> computeReachabilityTimes(Environment const& env, storm::logic::RewardMeasureType rewardMeasureType, CheckTask<storm::logic::EventuallyFormula, ValueType> const& checkTask) override;
};

223
src/storm/modelchecker/csl/helper/HybridMarkovAutomatonCslHelper.cpp
View File

@ -44,222 +44,40 @@ namespace storm {
return HybridMdpPrctlHelper<DdType, ValueType>::computeReachabilityRewards(env, dir, model, transitionMatrix, discretizedRewardModel, targetStates, qualitative);
}
/*
template<storm::dd::DdType DdType, class ValueType>
std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeUntilProbabilities(Environment const& env, storm::models::symbolic::MarkovAutomaton<DdType, ValueType> const& model, storm::dd::Add<DdType, ValueType> const& rateMatrix, storm::dd::Add<DdType, ValueType> const& exitRateVector, storm::dd::Bdd<DdType> const& phiStates, storm::dd::Bdd<DdType> const& psiStates, bool qualitative) {
return HybridMdpPrctlHelper<DdType, ValueType>::computeUntilProbabilities(env, model, computeProbabilityMatrix(rateMatrix, exitRateVector), phiStates, psiStates, qualitative);
}
template<storm::dd::DdType DdType, typename ValueType, typename std::enable_if<storm::NumberTraits<ValueType>::SupportsExponential, int>::type>
std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeBoundedUntilProbabilities(Environment const& env, storm::models::symbolic::MarkovAutomaton<DdType, ValueType> const& model, storm::dd::Add<DdType, ValueType> const& rateMatrix, storm::dd::Add<DdType, ValueType> const& exitRateVector, storm::dd::Bdd<DdType> const& phiStates, storm::dd::Bdd<DdType> const& psiStates, bool qualitative, double lowerBound, double upperBound) {
std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeBoundedUntilProbabilities(Environment const& env, OptimizationDirection dir, storm::models::symbolic::MarkovAutomaton<DdType, ValueType> const& model, storm::dd::Add<DdType, ValueType> const& transitionMatrix, storm::dd::Bdd<DdType> const& markovianStates, storm::dd::Add<DdType, ValueType> const& exitRateVector, storm::dd::Bdd<DdType> const& psiStates, bool qualitative, double lowerBound, double upperBound) {
// If the time bounds are [0, inf], we rather call untimed reachability.
if (storm::utility::isZero(lowerBound) && upperBound == storm::utility::infinity<ValueType>()) {
return computeUntilProbabilities(env, model, rateMatrix, exitRateVector, phiStates, psiStates, qualitative);
return storm::modelchecker::helper::HybridMdpPrctlHelper<DdType, ValueType>::computeUntilProbabilities(env, dir, model, transitionMatrix, psiStates.getDdManager().getBddOne(), psiStates, qualitative);
}
// From this point on, we know that we have to solve a more complicated problem [t, t'] with either t != 0
// or t' != inf.
// If we identify the states that have probability 0 of reaching the target states, we can exclude them from the
// further computations.
storm::dd::Bdd<DdType> statesWithProbabilityGreater0 = storm::utility::graph::performProbGreater0(model, rateMatrix.notZero(), phiStates, psiStates);
STORM_LOG_INFO("Found " << statesWithProbabilityGreater0.getNonZeroCount() << " states with probability greater 0.");
storm::dd::Bdd<DdType> statesWithProbabilityGreater0NonPsi = statesWithProbabilityGreater0 && !psiStates;
STORM_LOG_INFO("Found " << statesWithProbabilityGreater0NonPsi.getNonZeroCount() << " 'maybe' states.");
if (!statesWithProbabilityGreater0NonPsi.isZero()) {
// If the interval is of the form [0,0], we can return the result directly
if (storm::utility::isZero(upperBound)) {
// In this case, the interval is of the form [0, 0].
return std::unique_ptr<CheckResult>(new SymbolicQuantitativeCheckResult<DdType, ValueType>(model.getReachableStates(), psiStates.template toAdd<ValueType>()));
} else {
if (storm::utility::isZero(lowerBound)) {
// In this case, the interval is of the form [0, t].
// Note that this excludes [0, inf] since this is untimed reachability and we considered this case earlier.
// Find the maximal rate of all 'maybe' states to take it as the uniformization rate.
ValueType uniformizationRate = 1.02 * (statesWithProbabilityGreater0NonPsi.template toAdd<ValueType>() * exitRateVector).getMax();
STORM_LOG_THROW(uniformizationRate > 0, storm::exceptions::InvalidStateException, "The uniformization rate must be positive.");
// Compute the uniformized matrix.
storm::dd::Add<DdType, ValueType> uniformizedMatrix = computeUniformizedMatrix(model, rateMatrix, exitRateVector, statesWithProbabilityGreater0NonPsi, uniformizationRate);
// Compute the vector that is to be added as a compensation for removing the absorbing states.
storm::dd::Add<DdType, ValueType> b = (statesWithProbabilityGreater0NonPsi.template toAdd<ValueType>() * rateMatrix * psiStates.swapVariables(model.getRowColumnMetaVariablePairs()).template toAdd<ValueType>()).sumAbstract(model.getColumnVariables()) / model.getManager().getConstant(uniformizationRate);
storm::utility::Stopwatch conversionWatch(true);
// Create an ODD for the translation to an explicit representation.
storm::dd::Odd odd = statesWithProbabilityGreater0NonPsi.createOdd();
// Convert the symbolic parts to their explicit representation.
storm::storage::SparseMatrix<ValueType> explicitUniformizedMatrix = uniformizedMatrix.toMatrix(odd, odd);
std::vector<ValueType> explicitB = b.toVector(odd);
conversionWatch.stop();
STORM_LOG_INFO("Converting symbolic matrix/vector to explicit representation done in " << conversionWatch.getTimeInMilliseconds() << "ms.");
// Finally compute the transient probabilities.
std::vector<ValueType> values(statesWithProbabilityGreater0NonPsi.getNonZeroCount(), storm::utility::zero<ValueType>());
std::vector<ValueType> subresult = storm::modelchecker::helper::SparseMarkovAutomatonCslHelper::computeTransientProbabilities(env, explicitUniformizedMatrix, &explicitB, upperBound, uniformizationRate, values);
return std::unique_ptr<CheckResult>(new HybridQuantitativeCheckResult<DdType>(model.getReachableStates(),
(psiStates || !statesWithProbabilityGreater0) && model.getReachableStates(),
psiStates.template toAdd<ValueType>(), statesWithProbabilityGreater0NonPsi, odd, subresult));
} else if (upperBound == storm::utility::infinity<ValueType>()) {
// In this case, the interval is of the form [t, inf] with t != 0.
// Start by computing the (unbounded) reachability probabilities of reaching psi states while
// staying in phi states.
std::unique_ptr<CheckResult> unboundedResult = computeUntilProbabilities(env, model, rateMatrix, exitRateVector, phiStates, psiStates, qualitative);
// Compute the set of relevant states.
storm::dd::Bdd<DdType> relevantStates = statesWithProbabilityGreater0 && phiStates;
// Filter the unbounded result such that it only contains values for the relevant states.
unboundedResult->filter(SymbolicQualitativeCheckResult<DdType>(model.getReachableStates(), relevantStates));
storm::utility::Stopwatch conversionWatch;
// Build an ODD for the relevant states.
conversionWatch.start();
storm::dd::Odd odd = relevantStates.createOdd();
conversionWatch.stop();
std::vector<ValueType> result;
if (unboundedResult->isHybridQuantitativeCheckResult()) {
conversionWatch.start();
std::unique_ptr<CheckResult> explicitUnboundedResult = unboundedResult->asHybridQuantitativeCheckResult<DdType, ValueType>().toExplicitQuantitativeCheckResult();
conversionWatch.stop();
result = std::move(explicitUnboundedResult->asExplicitQuantitativeCheckResult<ValueType>().getValueVector());
} else {
STORM_LOG_THROW(unboundedResult->isSymbolicQuantitativeCheckResult(), storm::exceptions::InvalidStateException, "Expected check result of different type.");
result = unboundedResult->asSymbolicQuantitativeCheckResult<DdType, ValueType>().getValueVector().toVector(odd);
}
// Determine the uniformization rate for the transient probability computation.
ValueType uniformizationRate = 1.02 * (relevantStates.template toAdd<ValueType>() * exitRateVector).getMax();
// Compute the uniformized matrix.
storm::dd::Add<DdType, ValueType> uniformizedMatrix = computeUniformizedMatrix(model, rateMatrix, exitRateVector, relevantStates, uniformizationRate);
conversionWatch.start();
storm::storage::SparseMatrix<ValueType> explicitUniformizedMatrix = uniformizedMatrix.toMatrix(odd, odd);
conversionWatch.stop();
STORM_LOG_INFO("Converting symbolic matrix/vector to explicit representation done in " << conversionWatch.getTimeInMilliseconds() << "ms.");
// Compute the transient probabilities.
result = storm::modelchecker::helper::SparseMarkovAutomatonCslHelper::computeTransientProbabilities<ValueType>(env, explicitUniformizedMatrix, nullptr, lowerBound, uniformizationRate, result);
return std::unique_ptr<CheckResult>(new HybridQuantitativeCheckResult<DdType>(model.getReachableStates(), !relevantStates && model.getReachableStates(), model.getManager().template getAddZero<ValueType>(), relevantStates, odd, result));
} else {
// In this case, the interval is of the form [t, t'] with t != 0 and t' != inf.
if (lowerBound != upperBound) {
// In this case, the interval is of the form [t, t'] with t != 0, t' != inf and t != t'.
// Find the maximal rate of all 'maybe' states to take it as the uniformization rate.
ValueType uniformizationRate = 1.02 * (statesWithProbabilityGreater0NonPsi.template toAdd<ValueType>() * exitRateVector).getMax();
STORM_LOG_THROW(uniformizationRate > 0, storm::exceptions::InvalidStateException, "The uniformization rate must be positive.");
// Compute the (first) uniformized matrix.
storm::dd::Add<DdType, ValueType> uniformizedMatrix = computeUniformizedMatrix(model, rateMatrix, exitRateVector, statesWithProbabilityGreater0NonPsi, uniformizationRate);
// Create the one-step vector.
storm::dd::Add<DdType, ValueType> b = (statesWithProbabilityGreater0NonPsi.template toAdd<ValueType>() * rateMatrix * psiStates.swapVariables(model.getRowColumnMetaVariablePairs()).template toAdd<ValueType>()).sumAbstract(model.getColumnVariables()) / model.getManager().getConstant(uniformizationRate);
// Build an ODD for the relevant states and translate the symbolic parts to their explicit representation.
// If we reach this point, we convert this query to an instance for the sparse engine.
storm::utility::Stopwatch conversionWatch(true);
storm::dd::Odd odd = statesWithProbabilityGreater0NonPsi.createOdd();
storm::storage::SparseMatrix<ValueType> explicitUniformizedMatrix = uniformizedMatrix.toMatrix(odd, odd);
std::vector<ValueType> explicitB = b.toVector(odd);
conversionWatch.stop();
// Compute the transient probabilities.
std::vector<ValueType> values(statesWithProbabilityGreater0NonPsi.getNonZeroCount(), storm::utility::zero<ValueType>());
std::vector<ValueType> subResult = storm::modelchecker::helper::SparseMarkovAutomatonCslHelper::computeTransientProbabilities(env, explicitUniformizedMatrix, &explicitB, upperBound - lowerBound, uniformizationRate, values);
// Transform the explicit result to a hybrid check result, so we can easily convert it to
// a symbolic qualitative format.
HybridQuantitativeCheckResult<DdType> hybridResult(model.getReachableStates(), psiStates || (!statesWithProbabilityGreater0 && model.getReachableStates()),
psiStates.template toAdd<ValueType>(), statesWithProbabilityGreater0NonPsi, odd, subResult);
// Compute the set of relevant states.
storm::dd::Bdd<DdType> relevantStates = statesWithProbabilityGreater0 && phiStates;
// Filter the unbounded result such that it only contains values for the relevant states.
hybridResult.filter(SymbolicQualitativeCheckResult<DdType>(model.getReachableStates(), relevantStates));
// Build an ODD for the relevant states.
conversionWatch.start();
odd = relevantStates.createOdd();
std::unique_ptr<CheckResult> explicitResult = hybridResult.toExplicitQuantitativeCheckResult();
conversionWatch.stop();
std::vector<ValueType> newSubresult = std::move(explicitResult->asExplicitQuantitativeCheckResult<ValueType>().getValueVector());
// Then compute the transient probabilities of being in such a state after t time units. For this,
// we must re-uniformize the MarkovAutomaton, so we need to compute the second uniformized matrix.
uniformizationRate = 1.02 * (relevantStates.template toAdd<ValueType>() * exitRateVector).getMax();
STORM_LOG_THROW(uniformizationRate > 0, storm::exceptions::InvalidStateException, "The uniformization rate must be positive.");
// If the lower and upper bounds coincide, we have only determined the relevant states at this
// point, but we still need to construct the starting vector.
if (lowerBound == upperBound) {
odd = relevantStates.createOdd();
newSubresult = psiStates.template toAdd<ValueType>().toVector(odd);
}
// Finally, we compute the second set of transient probabilities.
uniformizedMatrix = computeUniformizedMatrix(model, rateMatrix, exitRateVector, relevantStates, uniformizationRate);
conversionWatch.start();
explicitUniformizedMatrix = uniformizedMatrix.toMatrix(odd, odd);
conversionWatch.stop();
STORM_LOG_INFO("Converting symbolic matrix/vector to explicit representation done in " << conversionWatch.getTimeInMilliseconds() << "ms.");
newSubresult = storm::modelchecker::helper::SparseMarkovAutomatonCslHelper::computeTransientProbabilities<ValueType>(env, explicitUniformizedMatrix, nullptr, lowerBound, uniformizationRate, newSubresult);
return std::unique_ptr<CheckResult>(new HybridQuantitativeCheckResult<DdType>(model.getReachableStates(), !relevantStates && model.getReachableStates(), model.getManager().template getAddZero<ValueType>(), relevantStates, odd, newSubresult));
} else {
// In this case, the interval is of the form [t, t] with t != 0, t != inf.
storm::utility::Stopwatch conversionWatch;
// Build an ODD for the relevant states.
conversionWatch.start();
storm::dd::Odd odd = statesWithProbabilityGreater0.createOdd();
std::vector<ValueType> newSubresult = psiStates.template toAdd<ValueType>().toVector(odd);
conversionWatch.stop();
// Then compute the transient probabilities of being in such a state after t time units. For this,
// we must re-uniformize the MarkovAutomaton, so we need to compute the second uniformized matrix.
ValueType uniformizationRate = 1.02 * (statesWithProbabilityGreater0.template toAdd<ValueType>() * exitRateVector).getMax();
STORM_LOG_THROW(uniformizationRate > 0, storm::exceptions::InvalidStateException, "The uniformization rate must be positive.");
// Finally, we compute the second set of transient probabilities.
storm::dd::Add<DdType, ValueType> uniformizedMatrix = computeUniformizedMatrix(model, rateMatrix, exitRateVector, statesWithProbabilityGreater0, uniformizationRate);
conversionWatch.start();
storm::storage::SparseMatrix<ValueType> explicitUniformizedMatrix = uniformizedMatrix.toMatrix(odd, odd);
// Create ODD for the translation.
storm::dd::Odd odd = model.getReachableStates().createOdd();
storm::storage::SparseMatrix<ValueType> explicitTransitionMatrix = transitionMatrix.toMatrix(model.getNondeterminismVariables(), odd, odd);
std::vector<ValueType> explicitExitRateVector = exitRateVector.toVector(odd);
conversionWatch.stop();
STORM_LOG_INFO("Converting symbolic matrix/vector to explicit representation done in " << conversionWatch.getTimeInMilliseconds() << "ms.");
newSubresult = storm::modelchecker::helper::SparseMarkovAutomatonCslHelper::computeTransientProbabilities<ValueType>(env, explicitUniformizedMatrix, nullptr, lowerBound, uniformizationRate, newSubresult);
STORM_LOG_INFO("Converting symbolic matrix to explicit representation done in " << conversionWatch.getTimeInMilliseconds() << "ms.");
return std::unique_ptr<CheckResult>(new HybridQuantitativeCheckResult<DdType>(model.getReachableStates(), !statesWithProbabilityGreater0 && model.getReachableStates(), model.getManager().template getAddZero<ValueType>(), statesWithProbabilityGreater0, odd, newSubresult));
}
}
}
} else {
return std::unique_ptr<CheckResult>(new SymbolicQuantitativeCheckResult<DdType>(model.getReachableStates(), psiStates.template toAdd<ValueType>()));
}
auto explicitResult = storm::modelchecker::helper::SparseMarkovAutomatonCslHelper::computeBoundedUntilProbabilities(env, dir, explicitTransitionMatrix, explicitExitRateVector, markovianStates.toVector(odd), psiStates.toVector(odd), {lowerBound, upperBound});
return std::unique_ptr<CheckResult>(new HybridQuantitativeCheckResult<DdType, ValueType>(model.getReachableStates(), model.getManager().getBddZero(), model.getManager().template getAddZero<ValueType>(), model.getReachableStates(), std::move(odd), std::move(explicitResult)));
}
template<storm::dd::DdType DdType, typename ValueType, typename std::enable_if<!storm::NumberTraits<ValueType>::SupportsExponential, int>::type>
std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeBoundedUntilProbabilities(Environment const& env, storm::models::symbolic::MarkovAutomaton<DdType, ValueType> const& model, storm::dd::Add<DdType, ValueType> const& rateMatrix, storm::dd::Add<DdType, ValueType> const& exitRateVector, storm::dd::Bdd<DdType> const& phiStates, storm::dd::Bdd<DdType> const& psiStates, bool qualitative, double lowerBound, double upperBound) {
std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeBoundedUntilProbabilities(Environment const&, OptimizationDirection, storm::models::symbolic::MarkovAutomaton<DdType, ValueType> const&, storm::dd::Add<DdType, ValueType> const&, storm::dd::Bdd<DdType> const&, storm::dd::Add<DdType, ValueType> const&, storm::dd::Bdd<DdType> const&, bool, double, double) {
STORM_LOG_THROW(false, storm::exceptions::InvalidOperationException, "Computing bounded until probabilities is unsupported for this value type.");
}
template<storm::dd::DdType DdType, class ValueType>
/* template<storm::dd::DdType DdType, class ValueType>
std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeLongRunAverageProbabilities(Environment const& env, storm::models::symbolic::MarkovAutomaton<DdType, ValueType> const& model, storm::dd::Add<DdType, ValueType> const& rateMatrix, storm::dd::Add<DdType, ValueType> const& exitRateVector, storm::dd::Bdd<DdType> const& psiStates) {
storm::utility::Stopwatch conversionWatch(true);
@ -303,24 +121,21 @@ namespace storm {
// Cudd, double.
template std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeReachabilityRewards(Environment const& env, OptimizationDirection dir, storm::models::symbolic::MarkovAutomaton<storm::dd::DdType::CUDD, double> const& model, storm::dd::Add<storm::dd::DdType::CUDD, double> const& transitionMatrix, storm::dd::Bdd<storm::dd::DdType::CUDD> const& markovianStates, storm::dd::Add<storm::dd::DdType::CUDD, double> const& exitRateVector, typename storm::models::symbolic::Model<storm::dd::DdType::CUDD, double>::RewardModelType const& rewardModel, storm::dd::Bdd<storm::dd::DdType::CUDD> const& targetStates, bool qualitative);
template std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeBoundedUntilProbabilities(Environment const& env, OptimizationDirection dir, storm::models::symbolic::MarkovAutomaton<storm::dd::DdType::CUDD, double> const& model, storm::dd::Add<storm::dd::DdType::CUDD, double> const& transitionMatrix, storm::dd::Bdd<storm::dd::DdType::CUDD> const& markovianStates, storm::dd::Add<storm::dd::DdType::CUDD, double> const& exitRateVector, storm::dd::Bdd<storm::dd::DdType::CUDD> const& psiStates, bool qualitative, double lowerBound, double upperBound);
/*
template std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeBoundedUntilProbabilities(Environment const& env, storm::models::symbolic::MarkovAutomaton<storm::dd::DdType::CUDD, double> const& model, storm::dd::Add<storm::dd::DdType::CUDD, double> const& rateMatrix, storm::dd::Add<storm::dd::DdType::CUDD, double> const& exitRateVector, storm::dd::Bdd<storm::dd::DdType::CUDD> const& phiStates, storm::dd::Bdd<storm::dd::DdType::CUDD> const& psiStates, bool qualitative, double lowerBound, double upperBound);
template std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeUntilProbabilities(Environment const& env, storm::models::symbolic::MarkovAutomaton<storm::dd::DdType::CUDD, double> const& model, storm::dd::Add<storm::dd::DdType::CUDD, double> const& rateMatrix, storm::dd::Add<storm::dd::DdType::CUDD, double> const& exitRateVector, storm::dd::Bdd<storm::dd::DdType::CUDD> const& phiStates, storm::dd::Bdd<storm::dd::DdType::CUDD> const& psiStates, bool qualitative);
template std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeLongRunAverageProbabilities(Environment const& env, storm::models::symbolic::MarkovAutomaton<storm::dd::DdType::CUDD, double> const& model, storm::dd::Add<storm::dd::DdType::CUDD, double> const& rateMatrix, storm::dd::Add<storm::dd::DdType::CUDD, double> const& exitRateVector, storm::dd::Bdd<storm::dd::DdType::CUDD> const& psiStates);
template std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeLongRunAverageRewards(Environment const& env, storm::models::symbolic::MarkovAutomaton<storm::dd::DdType::CUDD, double> const& model, storm::dd::Add<storm::dd::DdType::CUDD, double> const& rateMatrix, storm::dd::Add<storm::dd::DdType::CUDD, double> const& exitRateVector, typename storm::models::symbolic::Model<storm::dd::DdType::CUDD, double>::RewardModelType const& rewardModel);
*/
// Sylvan, double.
template std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeReachabilityRewards(Environment const& env, OptimizationDirection dir, storm::models::symbolic::MarkovAutomaton<storm::dd::DdType::Sylvan, double> const& model, storm::dd::Add<storm::dd::DdType::Sylvan, double> const& transitionMatrix, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& markovianStates, storm::dd::Add<storm::dd::DdType::Sylvan, double> const& exitRateVector, typename storm::models::symbolic::Model<storm::dd::DdType::Sylvan, double>::RewardModelType const& rewardModel, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& targetStates, bool qualitative);
/* template std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeBoundedUntilProbabilities(Environment const& env, storm::models::symbolic::MarkovAutomaton<storm::dd::DdType::Sylvan, double> const& model, storm::dd::Add<storm::dd::DdType::Sylvan, double> const& rateMatrix, storm::dd::Add<storm::dd::DdType::Sylvan, double> const& exitRateVector, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& phiStates, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& psiStates, bool qualitative, double lowerBound, double upperBound);
template std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeUntilProbabilities(Environment const& env, storm::models::symbolic::MarkovAutomaton<storm::dd::DdType::Sylvan, double> const& model, storm::dd::Add<storm::dd::DdType::Sylvan, double> const& rateMatrix, storm::dd::Add<storm::dd::DdType::Sylvan, double> const& exitRateVector, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& phiStates, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& psiStates, bool qualitative);
template std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeLongRunAverageProbabilities(Environment const& env, storm::models::symbolic::MarkovAutomaton<storm::dd::DdType::Sylvan, double> const& model, storm::dd::Add<storm::dd::DdType::Sylvan, double> const& rateMatrix, storm::dd::Add<storm::dd::DdType::Sylvan, double> const& exitRateVector, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& psiStates);
template std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeBoundedUntilProbabilities(Environment const& env, OptimizationDirection dir, storm::models::symbolic::MarkovAutomaton<storm::dd::DdType::Sylvan, double> const& model, storm::dd::Add<storm::dd::DdType::Sylvan, double> const& transitionMatrix, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& markovianStates, storm::dd::Add<storm::dd::DdType::Sylvan, double> const& exitRateVector, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& psiStates, bool qualitative, double lowerBound, double upperBound);
/* template std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeLongRunAverageProbabilities(Environment const& env, storm::models::symbolic::MarkovAutomaton<storm::dd::DdType::Sylvan, double> const& model, storm::dd::Add<storm::dd::DdType::Sylvan, double> const& rateMatrix, storm::dd::Add<storm::dd::DdType::Sylvan, double> const& exitRateVector, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& psiStates);
template std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeLongRunAverageRewards(Environment const& env, storm::models::symbolic::MarkovAutomaton<storm::dd::DdType::Sylvan, double> const& model, storm::dd::Add<storm::dd::DdType::Sylvan, double> const& rateMatrix, storm::dd::Add<storm::dd::DdType::Sylvan, double> const& exitRateVector, typename storm::models::symbolic::Model<storm::dd::DdType::Sylvan, double>::RewardModelType const& rewardModel);
*/
// Sylvan, rational number.
template std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeReachabilityRewards(Environment const& env, OptimizationDirection dir, storm::models::symbolic::MarkovAutomaton<storm::dd::DdType::Sylvan, storm::RationalNumber> const& model, storm::dd::Add<storm::dd::DdType::Sylvan, storm::RationalNumber> const& transitionMatrix, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& markovianStates, storm::dd::Add<storm::dd::DdType::Sylvan, storm::RationalNumber> const& exitRateVector, typename storm::models::symbolic::Model<storm::dd::DdType::Sylvan, storm::RationalNumber>::RewardModelType const& rewardModel, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& targetStates, bool qualitative);
/* template std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeBoundedUntilProbabilities(Environment const& env, storm::models::symbolic::MarkovAutomaton<storm::dd::DdType::Sylvan, storm::RationalNumber> const& model, storm::dd::Add<storm::dd::DdType::Sylvan, storm::RationalNumber> const& rateMatrix, storm::dd::Add<storm::dd::DdType::Sylvan, storm::RationalNumber> const& exitRateVector, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& phiStates, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& psiStates, bool qualitative, double lowerBound, double upperBound);
template std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeUntilProbabilities(Environment const& env, storm::models::symbolic::MarkovAutomaton<storm::dd::DdType::Sylvan, storm::RationalNumber> const& model, storm::dd::Add<storm::dd::DdType::Sylvan, storm::RationalNumber> const& rateMatrix, storm::dd::Add<storm::dd::DdType::Sylvan, storm::RationalNumber> const& exitRateVector, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& phiStates, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& psiStates, bool qualitative);
template std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeLongRunAverageProbabilities(Environment const& env, storm::models::symbolic::MarkovAutomaton<storm::dd::DdType::Sylvan, storm::RationalNumber> const& model, storm::dd::Add<storm::dd::DdType::Sylvan, storm::RationalNumber> const& rateMatrix, storm::dd::Add<storm::dd::DdType::Sylvan, storm::RationalNumber> const& exitRateVector, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& psiStates);
template std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeBoundedUntilProbabilities(Environment const& env, OptimizationDirection dir, storm::models::symbolic::MarkovAutomaton<storm::dd::DdType::Sylvan, storm::RationalNumber> const& model, storm::dd::Add<storm::dd::DdType::Sylvan, storm::RationalNumber> const& transitionMatrix, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& markovianStates, storm::dd::Add<storm::dd::DdType::Sylvan, storm::RationalNumber> const& exitRateVector, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& psiStates, bool qualitative, double lowerBound, double upperBound);
/* template std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeLongRunAverageProbabilities(Environment const& env, storm::models::symbolic::MarkovAutomaton<storm::dd::DdType::Sylvan, storm::RationalNumber> const& model, storm::dd::Add<storm::dd::DdType::Sylvan, storm::RationalNumber> const& rateMatrix, storm::dd::Add<storm::dd::DdType::Sylvan, storm::RationalNumber> const& exitRateVector, storm::dd::Bdd<storm::dd::DdType::Sylvan> const& psiStates);
template std::unique_ptr<CheckResult> HybridMarkovAutomatonCslHelper::computeLongRunAverageRewards(Environment const& env, storm::models::symbolic::MarkovAutomaton<storm::dd::DdType::Sylvan, storm::RationalNumber> const& model, storm::dd::Add<storm::dd::DdType::Sylvan, storm::RationalNumber> const& rateMatrix, storm::dd::Add<storm::dd::DdType::Sylvan, storm::RationalNumber> const& exitRateVector, typename storm::models::symbolic::Model<storm::dd::DdType::Sylvan, storm::RationalNumber>::RewardModelType const& rewardModel);
*/

15
src/storm/modelchecker/csl/helper/HybridMarkovAutomatonCslHelper.h
View File

@ -21,22 +21,11 @@ namespace storm {
template<storm::dd::DdType DdType, typename ValueType>
static std::unique_ptr<CheckResult> computeReachabilityRewards(Environment const& env, OptimizationDirection dir, storm::models::symbolic::MarkovAutomaton<DdType, ValueType> const& model, storm::dd::Add<DdType, ValueType> const& transitionMatrix, storm::dd::Bdd<DdType> const& markovianStates, storm::dd::Add<DdType, ValueType> const& exitRateVector, typename storm::models::symbolic::Model<DdType, ValueType>::RewardModelType const& rewardModel, storm::dd::Bdd<DdType> const& targetStates, bool qualitative);
/*
template<storm::dd::DdType DdType, typename ValueType, typename std::enable_if<storm::NumberTraits<ValueType>::SupportsExponential, int>::type = 0>
static std::unique_ptr<CheckResult> computeBoundedUntilProbabilities(Environment const& env, storm::models::symbolic::MarkovAutomaton<DdType, ValueType> const& model, storm::dd::Add<DdType, ValueType> const& rateMatrix, storm::dd::Add<DdType, ValueType> const& exitRateVector, storm::dd::Bdd<DdType> const& phiStates, storm::dd::Bdd<DdType> const& psiStates, bool qualitative, double lowerBound, double upperBound);
static std::unique_ptr<CheckResult> computeBoundedUntilProbabilities(Environment const& env, OptimizationDirection dir, storm::models::symbolic::MarkovAutomaton<DdType, ValueType> const& model, storm::dd::Add<DdType, ValueType> const& transitionMatrix, storm::dd::Bdd<DdType> const& markovianStates, storm::dd::Add<DdType, ValueType> const& exitRateVector, storm::dd::Bdd<DdType> const& psiStates, bool qualitative, double lowerBound, double upperBound);
template<storm::dd::DdType DdType, typename ValueType, typename std::enable_if<!storm::NumberTraits<ValueType>::SupportsExponential, int>::type = 0>
static std::unique_ptr<CheckResult> computeBoundedUntilProbabilities(Environment const& env, storm::models::symbolic::MarkovAutomaton<DdType, ValueType> const& model, storm::dd::Add<DdType, ValueType> const& rateMatrix, storm::dd::Add<DdType, ValueType> const& exitRateVector, storm::dd::Bdd<DdType> const& phiStates, storm::dd::Bdd<DdType> const& psiStates, bool qualitative, double lowerBound, double upperBound);
template<storm::dd::DdType DdType, typename ValueType>
static std::unique_ptr<CheckResult> computeUntilProbabilities(Environment const& env, storm::models::symbolic::MarkovAutomaton<DdType, ValueType> const& model, storm::dd::Add<DdType, ValueType> const& rateMatrix, storm::dd::Add<DdType, ValueType> const& exitRateVector, storm::dd::Bdd<DdType> const& phiStates, storm::dd::Bdd<DdType> const& psiStates, bool qualitative);
template<storm::dd::DdType DdType, typename ValueType>
static std::unique_ptr<CheckResult> computeLongRunAverageProbabilities(Environment const& env, storm::models::symbolic::MarkovAutomaton<DdType, ValueType> const& model, storm::dd::Add<DdType, ValueType> const& rateMatrix, storm::dd::Add<DdType, ValueType> const& exitRateVector, storm::dd::Bdd<DdType> const& psiStates);
template<storm::dd::DdType DdType, typename ValueType>
static std::unique_ptr<CheckResult> computeLongRunAverageRewards(Environment const& env, storm::models::symbolic::MarkovAutomaton<DdType, ValueType> const& model, storm::dd::Add<DdType, ValueType> const& rateMatrix, storm::dd::Add<DdType, ValueType> const& exitRateVector, typename storm::models::symbolic::Model<DdType, ValueType>::RewardModelType const& rewardModel);
*/
static std::unique_ptr<CheckResult> computeBoundedUntilProbabilities(Environment const& env, OptimizationDirection dir, storm::models::symbolic::MarkovAutomaton<DdType, ValueType> const& model, storm::dd::Add<DdType, ValueType> const& transitionMatrix, storm::dd::Bdd<DdType> const& markovianStates, storm::dd::Add<DdType, ValueType> const& exitRateVector, storm::dd::Bdd<DdType> const& psiStates, bool qualitative, double lowerBound, double upperBound);
};

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