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some modifications for preprocessing 

Former-commit-id: bee550a1d8
main
TimQu 9 years ago
parent
5310793653
commit
9ec10f7bcb
2 changed files with 53 additions and 60 deletions
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  1. 98
      src/modelchecker/multiobjective/helper/SparseMdpMultiObjectivePreprocessingHelper.cpp
  2. 15
      src/modelchecker/multiobjective/helper/SparseMultiObjectiveModelCheckerInformation.h

98
src/modelchecker/multiobjective/helper/SparseMdpMultiObjectivePreprocessingHelper.cpp
View File

@ -31,7 +31,7 @@ namespace storm {
addObjective(subFormula, info);
}
// Find out whether negated rewards should be considered.
setWhetherNegatedRewardsAreConsidered(info);
//setWhetherNegatedRewardsAreConsidered(info);
//Invoke preprocessing on objectives
for (auto& obj : info.objectives){
STORM_LOG_DEBUG("Preprocessing objective " << *obj.originalFormula << ".");
@ -57,25 +57,11 @@ namespace storm {
typename Information::ObjectiveInformation objective;
objective.originalFormula = formula;
storm::logic::OperatorFormula const& opFormula = formula->asOperatorFormula();
if(opFormula.hasBound()){
objective.threshold = opFormula.getBound().threshold;
objective.thresholdIsStrict = storm::logic::isStrict(opFormula.getBound().comparisonType);
// Note that we minimize if the comparison type is an upper bound since we are interested in the EXISTENCE of a scheduler.
objective.originalFormulaMinimizes = !storm::logic::isLowerBound(opFormula.getBound().comparisonType);
} else if (opFormula.hasOptimalityType()){
objective.thresholdIsStrict = false;
objective.originalFormulaMinimizes = storm::solver::minimize(opFormula.getOptimalityType());
} else {
STORM_LOG_THROW(false, storm::exceptions::InvalidPropertyException, "Current objective " << opFormula << " does not specify whether to minimize or maximize");
}
objective.rewardModelName = "objective" + std::to_string(info.objectives.size());
// Make sure the new reward model gets a unique name
while(info.preprocessedModel.hasRewardModel(objective.rewardModelName)){
objective.rewardModelName = "_" + objective.rewardModelName;
}
setStepBoundOfObjective(objective);
info.objectives.push_back(std::move(objective));
}
@ -102,7 +88,7 @@ namespace storm {
void SparseMdpMultiObjectivePreprocessingHelper<SparseMdpModelType>::setWhetherNegatedRewardsAreConsidered(Information& info) {
// Negative Rewards are considered whenever there is an unbounded reward objective that requires to minimize.
// If there is no unbounded reward objective, we make a majority vote.
uint_fast64_t numOfMinimizingObjectives = 0;
/* uint_fast64_t numOfMinimizingObjectives = 0;
for(auto const& obj : info.objectives){
if(obj.originalFormula->isRewardOperatorFormula() && !obj.stepBound){
info.negatedRewardsConsidered = obj.originalFormulaMinimizes;
@ -112,40 +98,24 @@ namespace storm {
}
// Reaching this point means that we make a majority vote
info.negatedRewardsConsidered = (numOfMinimizingObjectives*2) > info.objectives.size();
}
*/}
template<typename SparseMdpModelType>
void SparseMdpMultiObjectivePreprocessingHelper<SparseMdpModelType>::preprocessFormula(storm::logic::ProbabilityOperatorFormula const& formula, Information& info, typename Information::ObjectiveInformation& currentObjective) {
// We might need to adapt the threshold for the given objective
if(currentObjective.threshold) {
if(formula.getSubformula().isGloballyFormula()) {
// the threshold changes from e.g. '< p' to '>= 1-p'
currentObjective.threshold = storm::utility::one<double>() - *currentObjective.threshold;
currentObjective.thresholdIsStrict = !currentObjective.thresholdIsStrict;
if(!currentObjective.originalFormulaMinimizes) {
*(currentObjective.threshold) *= -storm::utility::one<ValueType>();
}
} else {
if(currentObjective.originalFormulaMinimizes) {
*(currentObjective.threshold) *= -storm::utility::one<ValueType>();
}
//Set the information for the objective
if(formula.hasBound()) {
currentObjective.threshold = formula.getBound().threshold;
currentObjective.thresholdIsStrict = storm::logic::isStrict(formula.getBound().comparisonType);
currentObjective.isNegative = !storm::logic::isLowerBound(formula.getBound().comparisonType);
if(currentObjective.isNegative) {
*currentObjective.threshold *= -storm::utility::one<double>();
}
} else if (formula.hasOptimalityType()){
currentObjective.isNegative = storm::solver::minimize(formula.getOptimalityType());
} else {
STORM_LOG_THROW(false, storm::exceptions::InvalidPropertyException, "Current objective " << formula << " does not specify whether to minimize or maximize");
}
/* Old version for the case that properties are flipped
// Check if we need to complement the property, e.g., P<0.3 [ F "a" ] ---> P >=0.7 [ G !"a" ]
// This is the case if the formula requires to minimize and positive rewards are considered or vice versa
if(info.negatedRewardsConsidered != currentObjective.originalFormulaMinimizes){
STORM_LOG_THROW(false, storm::exceptions::NotImplementedException, "Inverting of properties not supported yet");
//TODO
}
if(info.negatedRewardsConsidered && currentObjective.threshold){
*(currentObjective.threshold) *= -storm::utility::one<ValueType>();
}
*/
// Invoke preprocessing for subformula
if(formula.getSubformula().isUntilFormula()){
preprocessFormula(formula.getSubformula().asUntilFormula(), info, currentObjective);
@ -162,15 +132,25 @@ namespace storm {
template<typename SparseMdpModelType>
void SparseMdpMultiObjectivePreprocessingHelper<SparseMdpModelType>::preprocessFormula(storm::logic::RewardOperatorFormula const& formula, Information& info, typename Information::ObjectiveInformation& currentObjective) {
// Make sure that our decision for negative rewards is consistent with the formula
STORM_LOG_THROW(info.negatedRewardsConsidered == currentObjective.originalFormulaMinimizes, storm::exceptions::InvalidPropertyException, "Decided to consider " << (info.negatedRewardsConsidered ? "negated" : "non-negated") << "rewards, but the formula " << formula << (currentObjective.originalFormulaMinimizes ? " minimizes" : "maximizes") << ". Reward objectives should either all minimize or all maximize.");
//TODO Make sure that our decision for negative rewards is consistent with the formula
// STORM_LOG_THROW(info.negatedRewardsConsidered == currentObjective.originalFormulaMinimizes, storm::exceptions::InvalidPropertyException, "Decided to consider " << (info.negatedRewardsConsidered ? "negated" : "non-negated") << "rewards, but the formula " << formula << (currentObjective.originalFormulaMinimizes ? " minimizes" : "maximizes") << ". Reward objectives should either all minimize or all maximize.");
// Check if the reward model is uniquely specified
STORM_LOG_THROW((formula.hasRewardModelName() && info.preprocessedModel.hasRewardModel(formula.getRewardModelName()))
|| info.preprocessedModel.hasUniqueRewardModel(), storm::exceptions::InvalidPropertyException, "The reward model is not unique and the formula " << formula << " does not specify a reward model.");
if(info.negatedRewardsConsidered && currentObjective.threshold){
*(currentObjective.threshold) *= -storm::utility::one<ValueType>();
//Set the information for the objective
if(formula.hasBound()) {
currentObjective.threshold = formula.getBound().threshold;
currentObjective.thresholdIsStrict = storm::logic::isStrict(formula.getBound().comparisonType);
currentObjective.isNegative = !storm::logic::isLowerBound(formula.getBound().comparisonType);
if(currentObjective.isNegative) {
*currentObjective.threshold *= -storm::utility::one<double>();
}
} else if (formula.hasOptimalityType()){
currentObjective.isNegative = storm::solver::minimize(formula.getOptimalityType());
} else {
STORM_LOG_THROW(false, storm::exceptions::InvalidPropertyException, "Current objective " << formula << " does not specify whether to minimize or maximize");
}
// Invoke preprocessing for subformula
@ -213,7 +193,7 @@ namespace storm {
objectiveRewards[row] = info.preprocessedModel.getTransitionMatrix().getConstrainedRowSum(row, newPsiStates);
}
}
if(info.negatedRewardsConsidered){
if(currentObjective.isNegative){
storm::utility::vector::scaleVectorInPlace(objectiveRewards, -storm::utility::one<ValueType>());
}
info.preprocessedModel.addRewardModel(currentObjective.rewardModelName, RewardModelType(boost::none, objectiveRewards));
@ -221,12 +201,25 @@ namespace storm {
template<typename SparseMdpModelType>
void SparseMdpMultiObjectivePreprocessingHelper<SparseMdpModelType>::preprocessFormula(storm::logic::BoundedUntilFormula const& formula, Information& info, typename Information::ObjectiveInformation& currentObjective) {
STORM_LOG_THROW(formula.hasDiscreteTimeBound(), storm::exceptions::InvalidPropertyException, "Expected a boundedUntilFormula with a discrete time bound but got " << formula << ".");
currentObjective.stepBound = formula.getDiscreteTimeBound();
preprocessFormula(storm::logic::UntilFormula(formula.getLeftSubformula().asSharedPointer(), formula.getRightSubformula().asSharedPointer()), info, currentObjective);
}
template<typename SparseMdpModelType>
void SparseMdpMultiObjectivePreprocessingHelper<SparseMdpModelType>::preprocessFormula(storm::logic::GloballyFormula const& formula, Information& info, typename Information::ObjectiveInformation& currentObjective) {
// The formula will be transformed to an until formula for the complementary event
currentObjective.isInverted = true;
if(currentObjective.threshold) {
// the threshold changes from e.g. '> -p' to '>= 1-p' and '> p' to '>= p-1'
if(currentObjective.isNegative) {
*currentObjective.threshold += storm::utility::one<double>();
} else {
*currentObjective.threshold -= storm::utility::one<double>();
}
currentObjective.thresholdIsStrict = !currentObjective.thresholdIsStrict;
}
currentObjective.isNegative = !currentObjective.isNegative;
auto negatedSubformula = std::make_shared<storm::logic::UnaryBooleanStateFormula>(storm::logic::UnaryBooleanStateFormula::OperatorType::Not, formula.getSubformula().asSharedPointer());
preprocessFormula(storm::logic::UntilFormula(storm::logic::Formula::getTrueFormula(), negatedSubformula), info, currentObjective);
}
@ -257,7 +250,7 @@ namespace storm {
// Add a reward model that gives zero reward to the states of the second copy.
std::vector<ValueType> objectiveRewards = info.preprocessedModel.getRewardModel(optionalRewardModelName ? optionalRewardModelName.get() : "").getTotalRewardVector(info.preprocessedModel.getTransitionMatrix());
storm::utility::vector::setVectorValues(objectiveRewards, duplicatorResult.secondCopy, storm::utility::zero<ValueType>());
if(info.negatedRewardsConsidered){
if(currentObjective.isNegative){
storm::utility::vector::scaleVectorInPlace(objectiveRewards, -storm::utility::one<ValueType>());
}
info.preprocessedModel.addRewardModel(currentObjective.rewardModelName, RewardModelType(boost::none, objectiveRewards));
@ -265,8 +258,11 @@ namespace storm {
template<typename SparseMdpModelType>
void SparseMdpMultiObjectivePreprocessingHelper<SparseMdpModelType>::preprocessFormula(storm::logic::CumulativeRewardFormula const& formula, Information& info, typename Information::ObjectiveInformation& currentObjective, boost::optional<std::string> const& optionalRewardModelName) {
STORM_LOG_THROW(formula.hasDiscreteTimeBound(), storm::exceptions::InvalidPropertyException, "Expected a cumulativeRewardFormula with a discrete time bound but got " << formula << ".");
currentObjective.stepBound = formula.getDiscreteTimeBound();
std::vector<ValueType> objectiveRewards = info.preprocessedModel.getRewardModel(optionalRewardModelName ? optionalRewardModelName.get() : "").getTotalRewardVector(info.preprocessedModel.getTransitionMatrix());
if(info.negatedRewardsConsidered){
if(currentObjective.isNegative){
storm::utility::vector::scaleVectorInPlace(objectiveRewards, -storm::utility::one<ValueType>());
}
info.preprocessedModel.addRewardModel(currentObjective.rewardModelName, RewardModelType(boost::none, objectiveRewards));

15
src/modelchecker/multiobjective/helper/SparseMultiObjectiveModelCheckerInformation.h
View File

@ -21,16 +21,18 @@ namespace storm {
struct ObjectiveInformation {
std::shared_ptr<storm::logic::Formula const> originalFormula;
bool originalFormulaMinimizes;
boost::optional<double> threshold;
bool thresholdIsStrict;
std::string rewardModelName;
bool isNegative = false;
bool isInverted = false;
boost::optional<double> threshold;
bool thresholdIsStrict = false;
boost::optional<uint_fast64_t> stepBound;
void printInformationToStream(std::ostream& out) const {
out << std::setw(30) << originalFormula->toString();
out << " \t(";
out << (originalFormulaMinimizes ? "minimizes, \t" : "maximizes, \t");
out << (isNegative ? "-x, " : " ");
out << (isInverted ? "1-x, " : " ");
out << "intern threshold:";
if(threshold){
out << (thresholdIsStrict ? " >" : ">=");
@ -58,7 +60,6 @@ namespace storm {
SparseModelType preprocessedModel;
SparseModelType const& originalModel;
std::vector<uint_fast64_t> newToOldStateIndexMapping;
bool negatedRewardsConsidered;
std::vector<ObjectiveInformation> objectives;
@ -80,10 +81,6 @@ namespace storm {
out << "Preprocessed Model Information:" << std::endl;
preprocessedModel.printModelInformationToStream(out);
out << std::endl;
if(negatedRewardsConsidered){
out << "The rewards in the preprocessed model are negated" << std::endl;
out << std::endl;
}
out << "---------------------------------------------------------------------------------------------------------------------------------------" << std::endl;
}

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