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Implemented termination condition for parameter lifting checkers

tempestpy_adaptions
TimQu 8 years ago
parent
2dc976f9f9
commit
8c58008acf
2 changed files with 36 additions and 2 deletions
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  1. 19
      src/storm/modelchecker/parametric/SparseDtmcParameterLiftingModelChecker.cpp
  2. 19
      src/storm/modelchecker/parametric/SparseMdpParameterLiftingModelChecker.cpp

19
src/storm/modelchecker/parametric/SparseDtmcParameterLiftingModelChecker.cpp
View File

@ -147,12 +147,16 @@ namespace storm {
}
STORM_LOG_THROW(*stepBound > 0, storm::exceptions::NotSupportedException, "Can not apply parameter lifting on step bounded formula: The step bound has to be positive.");
//Every state is a maybeState
maybeStates = storm::storage::BitVector(this->parametricModel.getTransitionMatrix().getColumnCount(), true);
resultsForNonMaybeStates = std::vector<ConstantType>(this->parametricModel.getNumberOfStates());
// Create the reward vector
STORM_LOG_THROW((checkTask.isRewardModelSet() && this->parametricModel.hasRewardModel(checkTask.getRewardModel())) || (!checkTask.isRewardModelSet() && this->parametricModel.hasUniqueRewardModel()), storm::exceptions::InvalidPropertyException, "The reward model specified by the CheckTask is not available in the given model.");
typename SparseModelType::RewardModelType const& rewardModel = checkTask.isRewardModelSet() ? this->parametricModel.getRewardModel(checkTask.getRewardModel()) : this->parametricModel.getUniqueRewardModel();
std::vector<typename SparseModelType::ValueType> b = rewardModel.getTotalRewardVector(this->parametricModel.getTransitionMatrix());
parameterLifter = std::make_unique<storm::transformer::ParameterLifter<typename SparseModelType::ValueType, ConstantType>>(this->parametricModel.getTransitionMatrix(), b, storm::storage::BitVector(this->parametricModel.getTransitionMatrix().getRowCount(), true), storm::storage::BitVector(this->parametricModel.getTransitionMatrix().getColumnCount(), true));
parameterLifter = std::make_unique<storm::transformer::ParameterLifter<typename SparseModelType::ValueType, ConstantType>>(this->parametricModel.getTransitionMatrix(), b, maybeStates, maybeStates);
// We only know a lower bound for the result
@ -175,6 +179,19 @@ namespace storm {
if(upperResultBound) solver->setUpperBound(upperResultBound.get());
if(storm::solver::minimize(dirForParameters) && minSched && !stepBound) solver->setSchedulerHint(std::move(minSched.get()));
if(storm::solver::maximize(dirForParameters) && maxSched && !stepBound) solver->setSchedulerHint(std::move(maxSched.get()));
if (this->currentCheckTask->isBoundSet() && solver->hasSchedulerHint()) {
// If we reach this point, we know that after applying the hint, the x-values can only become larger (if we maximize) or smaller (if we minimize).
std::unique_ptr<storm::solver::TerminationCondition<ConstantType>> termCond;
storm::storage::BitVector relevantStatesInSubsystem = this->currentCheckTask->isOnlyInitialStatesRelevantSet() ? this->parametricModel.getInitialStates() % maybeStates : storm::storage::BitVector(maybeStates.getNumberOfSetBits(), true);
if (storm::solver::minimize(dirForParameters)) {
// Terminate if the value for ALL relevant states is already below the threshold
termCond = std::make_unique<storm::solver::TerminateIfFilteredExtremumBelowThreshold<ConstantType>> (relevantStatesInSubsystem, this->currentCheckTask->getBoundThreshold(), true, false);
} else {
// Terminate if the value for ALL relevant states is already above the threshold
termCond = std::make_unique<storm::solver::TerminateIfFilteredExtremumExceedsThreshold<ConstantType>> (relevantStatesInSubsystem, this->currentCheckTask->getBoundThreshold(), true, true);
}
solver->setTerminationCondition(std::move(termCond));
}
// Invoke the solver
if(stepBound) {

19
src/storm/modelchecker/parametric/SparseMdpParameterLiftingModelChecker.cpp
View File

@ -180,12 +180,16 @@ namespace storm {
}
STORM_LOG_THROW(*stepBound > 0, storm::exceptions::NotSupportedException, "Can not apply parameter lifting on step bounded formula: The step bound has to be positive.");
//Every state is a maybeState
maybeStates = storm::storage::BitVector(this->parametricModel.getTransitionMatrix().getColumnCount(), true);
resultsForNonMaybeStates = std::vector<ConstantType>(this->parametricModel.getNumberOfStates());
// Create the reward vector
STORM_LOG_THROW((checkTask.isRewardModelSet() && this->parametricModel.hasRewardModel(checkTask.getRewardModel())) || (!checkTask.isRewardModelSet() && this->parametricModel.hasUniqueRewardModel()), storm::exceptions::InvalidPropertyException, "The reward model specified by the CheckTask is not available in the given model.");
typename SparseModelType::RewardModelType const& rewardModel = checkTask.isRewardModelSet() ? this->parametricModel.getRewardModel(checkTask.getRewardModel()) : this->parametricModel.getUniqueRewardModel();
std::vector<typename SparseModelType::ValueType> b = rewardModel.getTotalRewardVector(this->parametricModel.getTransitionMatrix());
parameterLifter = std::make_unique<storm::transformer::ParameterLifter<typename SparseModelType::ValueType, ConstantType>>(this->parametricModel.getTransitionMatrix(), b, storm::storage::BitVector(this->parametricModel.getTransitionMatrix().getRowCount(), true), storm::storage::BitVector(this->parametricModel.getTransitionMatrix().getColumnCount(), true));
parameterLifter = std::make_unique<storm::transformer::ParameterLifter<typename SparseModelType::ValueType, ConstantType>>(this->parametricModel.getTransitionMatrix(), b, maybeStates, maybeStates);
applyPreviousResultAsHint = false;
@ -214,6 +218,19 @@ namespace storm {
} else {
x.assign(maybeStates.getNumberOfSetBits(), storm::utility::zero<ConstantType>());
}
if (this->currentCheckTask->isBoundSet() && this->currentCheckTask->getOptimizationDirection() == dirForParameters && solver->hasSchedulerHints()) {
// If we reach this point, we know that after applying the hints, the x-values can only become larger (if we maximize) or smaller (if we minimize).
std::unique_ptr<storm::solver::TerminationCondition<ConstantType>> termCond;
storm::storage::BitVector relevantStatesInSubsystem = this->currentCheckTask->isOnlyInitialStatesRelevantSet() ? this->parametricModel.getInitialStates() % maybeStates : storm::storage::BitVector(maybeStates.getNumberOfSetBits(), true);
if (storm::solver::minimize(dirForParameters)) {
// Terminate if the value for ALL relevant states is already below the threshold
termCond = std::make_unique<storm::solver::TerminateIfFilteredExtremumBelowThreshold<ConstantType>> (relevantStatesInSubsystem, this->currentCheckTask->getBoundThreshold(), true, false);
} else {
// Terminate if the value for ALL relevant states is already above the threshold
termCond = std::make_unique<storm::solver::TerminateIfFilteredExtremumExceedsThreshold<ConstantType>> (relevantStatesInSubsystem, this->currentCheckTask->getBoundThreshold(), true, true);
}
solver->setTerminationCondition(std::move(termCond));
}
// Invoke the solver
if(stepBound) {

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