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added and finalized methods for rpatlMC

tempestpy_adaptions
Stefan Pranger 4 years ago
parent
commit
72da4ba12e
  1. 59
      src/storm/modelchecker/rpatl/SparseSmgRpatlModelChecker.cpp

59
src/storm/modelchecker/rpatl/SparseSmgRpatlModelChecker.cpp

@ -2,6 +2,8 @@
#include <vector>
#include <memory>
#include <algorithm>
#include <boost/variant/get.hpp>
#include "storm/utility/macros.h"
#include "storm/utility/FilteredRewardModel.h"
@ -12,6 +14,10 @@
#include "storm/modelchecker/helper/utility/SetInformationFromCheckTask.h"
#include "storm/logic/FragmentSpecification.h"
#include "storm/logic/Coalition.h"
#include "storm/storage/BitVector.h"
#include "storm/environment/solver/MultiplierEnvironment.h"
#include "storm/models/sparse/StandardRewardModel.h"
@ -27,6 +33,8 @@ namespace storm {
// Intentionally left empty.
}
template<typename SparseSmgModelType>
bool SparseSmgRpatlModelChecker<SparseSmgModelType>::canHandleStatic(CheckTask<storm::logic::Formula, ValueType> const& checkTask, bool* requiresSingleInitialState) {
storm::logic::Formula const& formula = checkTask.getFormula();
@ -44,14 +52,46 @@ namespace storm {
}
}
template<typename SparseSmgModelType>
std::unique_ptr<CheckResult> SparseSmgRpatlModelChecker<SparseSmgModelType>::checkGameFormula(Environment const& env, CheckTask<storm::logic::GameFormula, ValueType> const& checkTask) {
storm::logic::GameFormula const& gameFormula = checkTask.getFormula();
storm::logic::Formula const& subFormula = gameFormula.getSubformula();
if (subFormula.isOperatorFormula()) {
return this->checkStateFormula(env, checkTask.substituteFormula(subFormula.asStateFormula()).setPlayerCoalition(gameFormula.getCoalition()));
if (subFormula.isRewardOperatorFormula()) {
return this->checkRewardOperatorFormula(solverEnv, checkTask.substituteFormula(subFormula.asRewardOperatorFormula()));
} else if (subFormula.isLongRunAverageOperatorFormula()) {
return this->checkLongRunAverageOperatorFormula(solverEnv, checkTask.substituteFormula(subFormula.asLongRunAverageOperatorFormula()));
}
STORM_LOG_THROW(false, storm::exceptions::NotImplementedException, "Cannot check this property (yet).");
}
template<typename ModelType>
std::unique_ptr<CheckResult> SparseSmgRpatlModelChecker<ModelType>::checkRewardOperatorFormula(Environment const& env, CheckTask<storm::logic::RewardOperatorFormula, ValueType> const& checkTask) {
storm::logic::RewardOperatorFormula const& formula = checkTask.getFormula();
std::unique_ptr<CheckResult> result = this->computeRewards(env, formula.getMeasureType(), checkTask.substituteFormula(formula.getSubformula()));
return result;
}
STORM_LOG_THROW(false, storm::exceptions::NotImplementedException, "Only game formulas with Operatorformulas as subformula are supported.");
template<typename ModelType>
std::unique_ptr<CheckResult> SparseSmgRpatlModelChecker<ModelType>::checkLongRunAverageOperatorFormula(Environment const& env, CheckTask<storm::logic::LongRunAverageOperatorFormula, ValueType> const& checkTask) {
storm::logic::LongRunAverageOperatorFormula const& formula = checkTask.getFormula();
std::unique_ptr<CheckResult> result = this->computeLongRunAverageProbabilities(env, checkTask.substituteFormula(formula.getSubformula().asStateFormula()));
return result;
}
template<typename ModelType>
std::unique_ptr<CheckResult> SparseSmgRpatlModelChecker<ModelType>::computeRewards(Environment const& env, storm::logic::RewardMeasureType rewardMeasureType, CheckTask<storm::logic::Formula, ValueType> const& checkTask) {
storm::logic::Formula const& rewardFormula = checkTask.getFormula();
if (rewardFormula.isLongRunAverageRewardFormula()) {
return this->computeLongRunAverageRewards(env, rewardMeasureType, checkTask.substituteFormula(rewardFormula.asLongRunAverageRewardFormula()));
}
STORM_LOG_THROW(false, storm::exceptions::InvalidArgumentException, "The given formula '" << rewardFormula << "' cannot (yet) be handled.");
}
template<typename SparseSmgModelType>
@ -62,10 +102,15 @@ namespace storm {
template<typename SparseSmgModelType>
std::unique_ptr<CheckResult> SparseSmgRpatlModelChecker<SparseSmgModelType>::computeLongRunAverageRewards(Environment const& env, storm::logic::RewardMeasureType rewardMeasureType, CheckTask<storm::logic::LongRunAverageRewardFormula, ValueType> const& checkTask) {
auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
STORM_LOG_THROW(checkTask.isPlayerCoalitionSet(), storm::exceptions::InvalidPropertyException, "No player coalition was set.");
auto coalitionStates = this->getModel().computeStatesOfCoalition(checkTask.getPlayerCoalition());
std::cout << "Found " << coalitionStates.getNumberOfSetBits() << " states in coalition." << std::endl;
STORM_LOG_THROW(false, storm::exceptions::NotImplementedException, "Not implemented.");
storm::modelchecker::helper::SparseNondeterministicGameInfiniteHorizonHelper<ValueType> helper(this->getModel().getTransitionMatrix(), this->getModel().getPlayerActionIndices());
storm::modelchecker::helper::setInformationFromCheckTaskNondeterministic(helper, checkTask, this->getModel());
auto values = helper.computeLongRunAverageRewards(env, rewardModel.get());
std::unique_ptr<CheckResult> result(new ExplicitQuantitativeCheckResult<ValueType>(std::move(values)));
if (checkTask.isProduceSchedulersSet()) {
result->asExplicitQuantitativeCheckResult<ValueType>().setScheduler(std::make_unique<storm::storage::Scheduler<ValueType>>(helper.extractScheduler()));
}
return result;
}
template class SparseSmgRpatlModelChecker<storm::models::sparse::Smg<double>>;

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