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Enabled Long Run Average Rewards for MAs (LP based)

tempestpy_adaptions
TimQu 8 years ago
parent
fd63603b5c
commit
6151dc0e96
4 changed files with 69 additions and 11 deletions
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  1. 8
      src/storm/modelchecker/csl/SparseMarkovAutomatonCslModelChecker.cpp
  2. 1
      src/storm/modelchecker/csl/SparseMarkovAutomatonCslModelChecker.h
  3. 54
      src/storm/modelchecker/csl/helper/SparseMarkovAutomatonCslHelper.cpp
  4. 11
      src/storm/modelchecker/csl/helper/SparseMarkovAutomatonCslHelper.h

8
src/storm/modelchecker/csl/SparseMarkovAutomatonCslModelChecker.cpp
View File

@ -107,6 +107,14 @@ namespace storm {
return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(std::move(result)));
}
template<typename SparseMarkovAutomatonModelType>
std::unique_ptr<CheckResult> SparseMarkovAutomatonCslModelChecker<SparseMarkovAutomatonModelType>::computeLongRunAverageRewards(storm::logic::RewardMeasureType rewardMeasureType, CheckTask<storm::logic::LongRunAverageRewardFormula, 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_LOG_THROW(this->getModel().isClosed(), storm::exceptions::InvalidPropertyException, "Unable to compute long run average rewards in non-closed Markov automaton.");
std::vector<ValueType> result = storm::modelchecker::helper::SparseMarkovAutomatonCslHelper::computeLongRunAverageRewards<ValueType, RewardModelType>(checkTask.getOptimizationDirection(), this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), this->getModel().getExitRates(), this->getModel().getMarkovianStates(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""), *minMaxLinearEquationSolverFactory);
return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(std::move(result)));
}
template<typename SparseMarkovAutomatonModelType>
std::unique_ptr<CheckResult> SparseMarkovAutomatonCslModelChecker<SparseMarkovAutomatonModelType>::computeReachabilityTimes(storm::logic::RewardMeasureType, CheckTask<storm::logic::EventuallyFormula, ValueType> const& checkTask) {
storm::logic::EventuallyFormula const& eventuallyFormula = checkTask.getFormula();

1
src/storm/modelchecker/csl/SparseMarkovAutomatonCslModelChecker.h
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@ -25,6 +25,7 @@ namespace storm {
virtual std::unique_ptr<CheckResult> computeUntilProbabilities(CheckTask<storm::logic::UntilFormula, ValueType> const& checkTask) override;
virtual std::unique_ptr<CheckResult> computeReachabilityRewards(storm::logic::RewardMeasureType rewardMeasureType, CheckTask<storm::logic::EventuallyFormula, ValueType> const& checkTask) override;
virtual std::unique_ptr<CheckResult> computeLongRunAverageProbabilities(CheckTask<storm::logic::StateFormula, ValueType> const& checkTask) override;
virtual std::unique_ptr<CheckResult> computeLongRunAverageRewards(storm::logic::RewardMeasureType rewardMeasureType, CheckTask<storm::logic::LongRunAverageRewardFormula, ValueType> const& checkTask) override;
virtual std::unique_ptr<CheckResult> computeReachabilityTimes(storm::logic::RewardMeasureType rewardMeasureType, CheckTask<storm::logic::EventuallyFormula, ValueType> const& checkTask) override;
virtual std::unique_ptr<CheckResult> checkMultiObjectiveFormula(CheckTask<storm::logic::MultiObjectiveFormula, ValueType> const& checkTask) override;

54
src/storm/modelchecker/csl/helper/SparseMarkovAutomatonCslHelper.cpp
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@ -214,6 +214,7 @@ namespace storm {
template<typename ValueType>
std::vector<ValueType> SparseMarkovAutomatonCslHelper::computeLongRunAverageProbabilities(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, storm::storage::SparseMatrix<ValueType> const& backwardTransitions, std::vector<ValueType> const& exitRateVector, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates, storm::solver::MinMaxLinearEquationSolverFactory<ValueType> const& minMaxLinearEquationSolverFactory) {
uint_fast64_t numberOfStates = transitionMatrix.getRowGroupCount();
// If there are no goal states, we avoid the computation and directly return zero.
@ -226,6 +227,36 @@ namespace storm {
return std::vector<ValueType>(numberOfStates, storm::utility::one<ValueType>());
}
// Otherwise, reduce the long run average probabilities to long run average rewards.
// Every Markovian goal state s gets 1/E(s) reward for its (unique) action.
std::vector<ValueType> totalActionRewards(transitionMatrix.getRowCount(), storm::utility::zero<ValueType>());
storm::storage::BitVector markovianGoalStates = markovianStates & psiStates;
for (auto const& state : markovianGoalStates) {
totalActionRewards[transitionMatrix.getRowGroupIndices()[state]] = storm::utility::one<ValueType>() / exitRateVector[state];
}
return computeLongRunAverageRewards(dir, transitionMatrix, backwardTransitions, exitRateVector, markovianStates, totalActionRewards, minMaxLinearEquationSolverFactory);
}
template<typename ValueType, typename RewardModelType>
std::vector<ValueType> SparseMarkovAutomatonCslHelper::computeLongRunAverageRewards(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, storm::storage::SparseMatrix<ValueType> const& backwardTransitions, std::vector<ValueType> const& exitRateVector, storm::storage::BitVector const& markovianStates, RewardModelType const& rewardModel, storm::solver::MinMaxLinearEquationSolverFactory<ValueType> const& minMaxLinearEquationSolverFactory) {
// Obtain the total action reward vector where the state rewards are scaled accordingly
std::vector<ValueType> stateRewardWeights(transitionMatrix.getRowGroupCount(), storm::utility::zero<ValueType>());
for (auto const markovianState : markovianStates) {
stateRewardWeights[markovianState] = storm::utility::one<ValueType>() / exitRateVector[markovianState];
}
std::vector<ValueType> totalRewardVector = rewardModel.getTotalActionRewardVector(transitionMatrix, stateRewardWeights);
RewardModelType scaledRewardModel(boost::none, std::move(totalRewardVector));
return computeLongRunAverageRewards(dir, transitionMatrix, backwardTransitions, exitRateVector, markovianStates, totalRewardVector, minMaxLinearEquationSolverFactory);
}
template<typename ValueType>
std::vector<ValueType> SparseMarkovAutomatonCslHelper::computeLongRunAverageRewards(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, storm::storage::SparseMatrix<ValueType> const& backwardTransitions, std::vector<ValueType> const& exitRateVector, storm::storage::BitVector const& markovianStates, std::vector<ValueType> const& totalActionRewards, storm::solver::MinMaxLinearEquationSolverFactory<ValueType> const& minMaxLinearEquationSolverFactory) {
uint_fast64_t numberOfStates = transitionMatrix.getRowGroupCount();
// Start by decomposing the Markov automaton into its MECs.
storm::storage::MaximalEndComponentDecomposition<ValueType> mecDecomposition(transitionMatrix, backwardTransitions);
@ -251,7 +282,7 @@ namespace storm {
}
// Compute the LRA value for the current MEC.
lraValuesForEndComponents.push_back(computeLraForMaximalEndComponent(dir, transitionMatrix, exitRateVector, markovianStates, psiStates, mec));
lraValuesForEndComponents.push_back(computeLraForMaximalEndComponent(dir, transitionMatrix, exitRateVector, markovianStates, totalActionRewards, mec));
}
// For fast transition rewriting, we build some auxiliary data structures.
@ -381,7 +412,7 @@ namespace storm {
}
template<typename ValueType>
ValueType SparseMarkovAutomatonCslHelper::computeLraForMaximalEndComponent(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, std::vector<ValueType> const& exitRateVector, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& goalStates, storm::storage::MaximalEndComponent const& mec) {
ValueType SparseMarkovAutomatonCslHelper::computeLraForMaximalEndComponent(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, std::vector<ValueType> const& exitRateVector, storm::storage::BitVector const& markovianStates, std::vector<ValueType> const& totalActionRewards, storm::storage::MaximalEndComponent const& mec) {
std::unique_ptr<storm::utility::solver::LpSolverFactory> lpSolverFactory(new storm::utility::solver::LpSolverFactory());
std::unique_ptr<storm::solver::LpSolver> solver = lpSolverFactory->create("LRA for MEC");
solver->setOptimizationDirection(invert(dir));
@ -402,6 +433,9 @@ namespace storm {
// Now, based on the type of the state, create a suitable constraint.
if (markovianStates.get(state)) {
STORM_LOG_ASSERT(stateChoicesPair.second.size() == 1, "Markovian state " << state << " is not deterministic: It has " << stateChoicesPair.second.size() << " choices.");
uint_fast64_t choice = *stateChoicesPair.second.begin();
storm::expressions::Expression constraint = stateToVariableMap.at(state);
for (auto element : transitionMatrix.getRow(nondeterministicChoiceIndices[state])) {
@ -409,7 +443,7 @@ namespace storm {
}
constraint = constraint + solver->getManager().rational(storm::utility::one<ValueType>() / exitRateVector[state]) * k;
storm::expressions::Expression rightHandSide = goalStates.get(state) ? solver->getManager().rational(storm::utility::one<ValueType>() / exitRateVector[state]) : solver->getManager().rational(storm::utility::zero<ValueType>());
storm::expressions::Expression rightHandSide = solver->getManager().rational(totalActionRewards[choice]);
if (dir == OptimizationDirection::Minimize) {
constraint = constraint <= rightHandSide;
} else {
@ -426,7 +460,7 @@ namespace storm {
constraint = constraint - stateToVariableMap.at(element.getColumn()) * solver->getManager().rational(element.getValue());
}
storm::expressions::Expression rightHandSide = solver->getManager().rational(storm::utility::zero<ValueType>());
storm::expressions::Expression rightHandSide = solver->getManager().rational(totalActionRewards[choice]);
if (dir == OptimizationDirection::Minimize) {
constraint = constraint <= rightHandSide;
} else {
@ -451,11 +485,15 @@ namespace storm {
template std::vector<double> SparseMarkovAutomatonCslHelper::computeLongRunAverageProbabilities(OptimizationDirection dir, storm::storage::SparseMatrix<double> const& transitionMatrix, storm::storage::SparseMatrix<double> const& backwardTransitions, std::vector<double> const& exitRateVector, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates, storm::solver::MinMaxLinearEquationSolverFactory<double> const& minMaxLinearEquationSolverFactory);
template std::vector<double> SparseMarkovAutomatonCslHelper::computeLongRunAverageRewards(OptimizationDirection dir, storm::storage::SparseMatrix<double> const& transitionMatrix, storm::storage::SparseMatrix<double> const& backwardTransitions, std::vector<double> const& exitRateVector, storm::storage::BitVector const& markovianStates, storm::models::sparse::StandardRewardModel<double> const& rewardModel, storm::solver::MinMaxLinearEquationSolverFactory<double> const& minMaxLinearEquationSolverFactory);
template std::vector<double> SparseMarkovAutomatonCslHelper::computeLongRunAverageRewards(OptimizationDirection dir, storm::storage::SparseMatrix<double> const& transitionMatrix, storm::storage::SparseMatrix<double> const& backwardTransitions, std::vector<double> const& exitRateVector, storm::storage::BitVector const& markovianStates, std::vector<double> const& totalActionRewards, storm::solver::MinMaxLinearEquationSolverFactory<double> const& minMaxLinearEquationSolverFactory);
template std::vector<double> SparseMarkovAutomatonCslHelper::computeReachabilityTimes(OptimizationDirection dir, storm::storage::SparseMatrix<double> const& transitionMatrix, storm::storage::SparseMatrix<double> const& backwardTransitions, std::vector<double> const& exitRateVector, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates, storm::solver::MinMaxLinearEquationSolverFactory<double> const& minMaxLinearEquationSolverFactory);
template void SparseMarkovAutomatonCslHelper::computeBoundedReachabilityProbabilities(OptimizationDirection dir, storm::storage::SparseMatrix<double> const& transitionMatrix, std::vector<double> const& exitRates, storm::storage::BitVector const& goalStates, storm::storage::BitVector const& markovianNonGoalStates, storm::storage::BitVector const& probabilisticNonGoalStates, std::vector<double>& markovianNonGoalValues, std::vector<double>& probabilisticNonGoalValues, double delta, uint_fast64_t numberOfSteps, storm::solver::MinMaxLinearEquationSolverFactory<double> const& minMaxLinearEquationSolverFactory);
template double SparseMarkovAutomatonCslHelper::computeLraForMaximalEndComponent(OptimizationDirection dir, storm::storage::SparseMatrix<double> const& transitionMatrix, std::vector<double> const& exitRateVector, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& goalStates, storm::storage::MaximalEndComponent const& mec);
template double SparseMarkovAutomatonCslHelper::computeLraForMaximalEndComponent(OptimizationDirection dir, storm::storage::SparseMatrix<double> const& transitionMatrix, std::vector<double> const& exitRateVector, storm::storage::BitVector const& markovianStates, std::vector<double> const& totalActionRewards, storm::storage::MaximalEndComponent const& mec);
template std::vector<storm::RationalNumber> SparseMarkovAutomatonCslHelper::computeBoundedUntilProbabilities(OptimizationDirection dir, storm::storage::SparseMatrix<storm::RationalNumber> const& transitionMatrix, std::vector<storm::RationalNumber> const& exitRateVector, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates, std::pair<double, double> const& boundsPair, storm::solver::MinMaxLinearEquationSolverFactory<storm::RationalNumber> const& minMaxLinearEquationSolverFactory);
@ -465,11 +503,15 @@ namespace storm {
template std::vector<storm::RationalNumber> SparseMarkovAutomatonCslHelper::computeLongRunAverageProbabilities(OptimizationDirection dir, storm::storage::SparseMatrix<storm::RationalNumber> const& transitionMatrix, storm::storage::SparseMatrix<storm::RationalNumber> const& backwardTransitions, std::vector<storm::RationalNumber> const& exitRateVector, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates, storm::solver::MinMaxLinearEquationSolverFactory<storm::RationalNumber> const& minMaxLinearEquationSolverFactory);
template std::vector<storm::RationalNumber> SparseMarkovAutomatonCslHelper::computeLongRunAverageRewards(OptimizationDirection dir, storm::storage::SparseMatrix<storm::RationalNumber> const& transitionMatrix, storm::storage::SparseMatrix<storm::RationalNumber> const& backwardTransitions, std::vector<storm::RationalNumber> const& exitRateVector, storm::storage::BitVector const& markovianStates, storm::models::sparse::StandardRewardModel<storm::RationalNumber> const& rewardModel, storm::solver::MinMaxLinearEquationSolverFactory<storm::RationalNumber> const& minMaxLinearEquationSolverFactory);
template std::vector<storm::RationalNumber> SparseMarkovAutomatonCslHelper::computeLongRunAverageRewards(OptimizationDirection dir, storm::storage::SparseMatrix<storm::RationalNumber> const& transitionMatrix, storm::storage::SparseMatrix<storm::RationalNumber> const& backwardTransitions, std::vector<storm::RationalNumber> const& exitRateVector, storm::storage::BitVector const& markovianStates, std::vector<storm::RationalNumber> const& totalActionRewards, storm::solver::MinMaxLinearEquationSolverFactory<storm::RationalNumber> const& minMaxLinearEquationSolverFactory);
template std::vector<storm::RationalNumber> SparseMarkovAutomatonCslHelper::computeReachabilityTimes(OptimizationDirection dir, storm::storage::SparseMatrix<storm::RationalNumber> const& transitionMatrix, storm::storage::SparseMatrix<storm::RationalNumber> const& backwardTransitions, std::vector<storm::RationalNumber> const& exitRateVector, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates, storm::solver::MinMaxLinearEquationSolverFactory<storm::RationalNumber> const& minMaxLinearEquationSolverFactory);
template void SparseMarkovAutomatonCslHelper::computeBoundedReachabilityProbabilities(OptimizationDirection dir, storm::storage::SparseMatrix<storm::RationalNumber> const& transitionMatrix, std::vector<storm::RationalNumber> const& exitRates, storm::storage::BitVector const& goalStates, storm::storage::BitVector const& markovianNonGoalStates, storm::storage::BitVector const& probabilisticNonGoalStates, std::vector<storm::RationalNumber>& markovianNonGoalValues, std::vector<storm::RationalNumber>& probabilisticNonGoalValues, storm::RationalNumber delta, uint_fast64_t numberOfSteps, storm::solver::MinMaxLinearEquationSolverFactory<storm::RationalNumber> const& minMaxLinearEquationSolverFactory);
template storm::RationalNumber SparseMarkovAutomatonCslHelper::computeLraForMaximalEndComponent(OptimizationDirection dir, storm::storage::SparseMatrix<storm::RationalNumber> const& transitionMatrix, std::vector<storm::RationalNumber> const& exitRateVector, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& goalStates, storm::storage::MaximalEndComponent const& mec);
template storm::RationalNumber SparseMarkovAutomatonCslHelper::computeLraForMaximalEndComponent(OptimizationDirection dir, storm::storage::SparseMatrix<storm::RationalNumber> const& transitionMatrix, std::vector<storm::RationalNumber> const& exitRateVector, storm::storage::BitVector const& markovianStates, std::vector<storm::RationalNumber> const& totalActionRewards, storm::storage::MaximalEndComponent const& mec);
}
}

11
src/storm/modelchecker/csl/helper/SparseMarkovAutomatonCslHelper.h
View File

@ -31,6 +31,12 @@ namespace storm {
template <typename ValueType>
static std::vector<ValueType> computeLongRunAverageProbabilities(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, storm::storage::SparseMatrix<ValueType> const& backwardTransitions, std::vector<ValueType> const& exitRateVector, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates, storm::solver::MinMaxLinearEquationSolverFactory<ValueType> const& minMaxLinearEquationSolverFactory);
template <typename ValueType, typename RewardModelType>
static std::vector<ValueType> computeLongRunAverageRewards(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, storm::storage::SparseMatrix<ValueType> const& backwardTransitions, std::vector<ValueType> const& exitRateVector, storm::storage::BitVector const& markovianStates, RewardModelType const& rewardModel, storm::solver::MinMaxLinearEquationSolverFactory<ValueType> const& minMaxLinearEquationSolverFactory);
template <typename ValueType>
static std::vector<ValueType> computeLongRunAverageRewards(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, storm::storage::SparseMatrix<ValueType> const& backwardTransitions, std::vector<ValueType> const& exitRateVector, storm::storage::BitVector const& markovianStates, std::vector<ValueType> const& totalActionRewards, storm::solver::MinMaxLinearEquationSolverFactory<ValueType> const& minMaxLinearEquationSolverFactory);
template <typename ValueType>
static std::vector<ValueType> computeReachabilityTimes(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, storm::storage::SparseMatrix<ValueType> const& backwardTransitions, std::vector<ValueType> const& exitRateVector, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates, storm::solver::MinMaxLinearEquationSolverFactory<ValueType> const& minMaxLinearEquationSolverFactory);
@ -49,12 +55,13 @@ namespace storm {
* @param markovianStates A bit vector storing all markovian states.
* @param exitRateVector A vector with exit rates for all states. Exit rates of probabilistic states are
* assumed to be zero.
* @param goalStates A bit vector indicating which states are to be considered as goal states.
* @param totalActionRewards A vector indicating the total rewards obtained for each action
* @param mec The maximal end component to consider for computing the long-run average.
* @return The long-run average of being in a goal state for the given MEC.
*/
template <typename ValueType>
static ValueType computeLraForMaximalEndComponent(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, std::vector<ValueType> const& exitRateVector, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& goalStates, storm::storage::MaximalEndComponent const& mec);
static ValueType computeLraForMaximalEndComponent(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, std::vector<ValueType> const& exitRateVector, storm::storage::BitVector const& markovianStates, std::vector<ValueType> const& totalActionRewards, storm::storage::MaximalEndComponent const& mec);
};
}

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