TimQu
8 years ago
5 changed files with 315 additions and 6 deletions
-
101src/modelchecker/multiobjective/pcaa/SparsePcaaAchievabilityQuery.cpp
-
58src/modelchecker/multiobjective/pcaa/SparsePcaaAchievabilityQuery.h
-
101src/modelchecker/multiobjective/pcaa/SparsePcaaParetoQuery.cpp
-
47src/modelchecker/multiobjective/pcaa/SparsePcaaParetoQuery.h
-
14test/functional/transformer/EndComponentEliminatorTest.cpp
@ -0,0 +1,101 @@ |
|||
#include "src/modelchecker/multiobjective/pcaa/SparsePcaaAchievabilityQuery.h"
|
|||
|
|||
#include "src/adapters/CarlAdapter.h"
|
|||
#include "src/models/sparse/Mdp.h"
|
|||
#include "src/models/sparse/MarkovAutomaton.h"
|
|||
#include "src/models/sparse/StandardRewardModel.h"
|
|||
#include "src/modelchecker/results/ExplicitQualitativeCheckResult.h"
|
|||
#include "src/utility/constants.h"
|
|||
#include "src/utility/vector.h"
|
|||
#include "src/settings//SettingsManager.h"
|
|||
#include "src/settings/modules/GeneralSettings.h"
|
|||
#include "src/settings/modules/MultiObjectiveSettings.h"
|
|||
|
|||
namespace storm { |
|||
namespace modelchecker { |
|||
namespace multiobjective { |
|||
|
|||
|
|||
template <class SparseModelType, typename GeometryValueType> |
|||
SparsePcaaAchievabilityQuery<SparseModelType, GeometryValueType>::SparsePcaaAchievabilityQuery(SparsePcaaPreprocessorReturnType<SparseModelType>& preprocessorResult) : SparsePcaaQuery<SparseModelType, GeometryValueType>(preprocessorResult) { |
|||
STORM_LOG_ASSERT(preprocessorResult.queryType==SparsePcaaPreprocessorReturnType<SparseModelType>::QueryType::Achievability, "Invalid query Type"); |
|||
initializeThresholdData(); |
|||
|
|||
// Set the maximum gap between lower and upper bound of the weightVectorChecker result.
|
|||
// This is the maximal edge length of the box we have to consider around each computed point
|
|||
// We pick the gap such that the maximal distance between two points within this box is less than the given precision divided by two.
|
|||
typename SparseModelType::ValueType gap = storm::utility::convertNumber<typename SparseModelType::ValueType>(storm::settings::getModule<storm::settings::modules::MultiObjectiveSettings>().getPrecision()); |
|||
gap /= (storm::utility::one<typename SparseModelType::ValueType>() + storm::utility::one<typename SparseModelType::ValueType>()); |
|||
gap /= storm::utility::sqrt(static_cast<typename SparseModelType::ValueType>(this->objectives.size())); |
|||
this->weightVectorChecker->setMaximumLowerUpperBoundGap(gap); |
|||
|
|||
} |
|||
|
|||
template <class SparseModelType, typename GeometryValueType> |
|||
void SparsePcaaAchievabilityQuery<SparseModelType, GeometryValueType>::initializeThresholdData() { |
|||
thresholds.reserve(this->objectives.size()); |
|||
strictThresholds = storm::storage::BitVector(this->objectives.size(), false); |
|||
for(uint_fast64_t objIndex = 0; objIndex < this->objectives.size(); ++objIndex) { |
|||
thresholds.push_back(storm::utility::convertNumber<GeometryValueType>(*this->objectives[objIndex].threshold)); |
|||
strictThresholds.set(objIndex, this->objectives[objIndex].thresholdIsStrict); |
|||
} |
|||
} |
|||
|
|||
template <class SparseModelType, typename GeometryValueType> |
|||
std::unique_ptr<CheckResult> SparsePcaaAchievabilityQuery<SparseModelType, GeometryValueType>::check() { |
|||
|
|||
bool result = this->checkAchievability(); |
|||
|
|||
return std::unique_ptr<CheckResult>(new ExplicitQualitativeCheckResult(this->originalModel.getInitialStates().getNextSetIndex(0), result)); |
|||
|
|||
} |
|||
|
|||
template <class SparseModelType, typename GeometryValueType> |
|||
bool SparsePcaaAchievabilityQuery<SparseModelType, GeometryValueType>::checkAchievability() { |
|||
// repeatedly refine the over/ under approximation until the threshold point is either in the under approx. or not in the over approx.
|
|||
while(!this->maxStepsPerformed()){ |
|||
WeightVector separatingVector = this->findSeparatingVector(thresholds); |
|||
this->performRefinementStep(std::move(separatingVector)); |
|||
if(!checkIfThresholdsAreSatisfied(this->overApproximation)){ |
|||
return false; |
|||
} |
|||
if(checkIfThresholdsAreSatisfied(this->underApproximation)){ |
|||
return true; |
|||
} |
|||
} |
|||
STORM_LOG_ERROR("Could not check whether thresholds are achievable: Exceeded maximum number of refinement steps"); |
|||
return false; |
|||
} |
|||
|
|||
|
|||
template <class SparseModelType, typename GeometryValueType> |
|||
bool SparsePcaaAchievabilityQuery<SparseModelType, GeometryValueType>::checkIfThresholdsAreSatisfied(std::shared_ptr<storm::storage::geometry::Polytope<GeometryValueType>> const& polytope) { |
|||
std::vector<storm::storage::geometry::Halfspace<GeometryValueType>> halfspaces = polytope->getHalfspaces(); |
|||
for(auto const& h : halfspaces) { |
|||
GeometryValueType distance = h.distance(thresholds); |
|||
if(distance < storm::utility::zero<GeometryValueType>()) { |
|||
return false; |
|||
} |
|||
if(distance == storm::utility::zero<GeometryValueType>()) { |
|||
// In this case, the thresholds point is on the boundary of the polytope.
|
|||
// Check if this is problematic for the strict thresholds
|
|||
for(auto strictThreshold : strictThresholds) { |
|||
if(h.normalVector()[strictThreshold] > storm::utility::zero<GeometryValueType>()) { |
|||
return false; |
|||
} |
|||
} |
|||
} |
|||
} |
|||
return true; |
|||
} |
|||
|
|||
#ifdef STORM_HAVE_CARL
|
|||
template class SparsePcaaAchievabilityQuery<storm::models::sparse::Mdp<double>, storm::RationalNumber>; |
|||
template class SparsePcaaAchievabilityQuery<storm::models::sparse::MarkovAutomaton<double>, storm::RationalNumber>; |
|||
|
|||
template class SparsePcaaAchievabilityQuery<storm::models::sparse::Mdp<storm::RationalNumber>, storm::RationalNumber>; |
|||
// template class SparsePcaaAchievabilityQuery<storm::models::sparse::MarkovAutomaton<storm::RationalNumber>, storm::RationalNumber>;
|
|||
#endif
|
|||
} |
|||
} |
|||
} |
@ -0,0 +1,58 @@ |
|||
#ifndef STORM_MODELCHECKER_MULTIOBJECTIVE_PCAA_SPARSEPCAAACHIEVABILITYQUERY_H_ |
|||
#define STORM_MODELCHECKER_MULTIOBJECTIVE_PCAA_SPARSEPCAAACHIEVABILITYQUERY_H_ |
|||
|
|||
#include "src/modelchecker/multiobjective/pcaa/SparsePcaaQuery.h" |
|||
|
|||
namespace storm { |
|||
namespace modelchecker { |
|||
namespace multiobjective { |
|||
|
|||
/* |
|||
* This class represents a query for the Pareto curve approximation algorithm (Pcaa). |
|||
* It implements the necessary computations for the different query types. |
|||
*/ |
|||
template <class SparseModelType, typename GeometryValueType> |
|||
class SparsePcaaAchievabilityQuery : public SparsePcaaQuery<SparseModelType, GeometryValueType> { |
|||
public: |
|||
|
|||
// Typedefs for simple geometric objects |
|||
typedef std::vector<GeometryValueType> Point; |
|||
typedef std::vector<GeometryValueType> WeightVector; |
|||
|
|||
/* |
|||
* Creates a new query for the Pareto curve approximation algorithm (Pcaa) |
|||
* @param preprocessorResult the result from preprocessing |
|||
*/ |
|||
SparsePcaaAchievabilityQuery(SparsePcaaPreprocessorReturnType<SparseModelType>& preprocessorResult); |
|||
|
|||
|
|||
/* |
|||
* Invokes the computation and retrieves the result |
|||
*/ |
|||
virtual std::unique_ptr<CheckResult> check() override; |
|||
|
|||
private: |
|||
|
|||
void initializeThresholdData(); |
|||
|
|||
/* |
|||
* Returns whether the given thresholds are achievable. |
|||
*/ |
|||
bool checkAchievability(); |
|||
|
|||
/* |
|||
* Returns true iff there is one point in the given polytope that satisfies the given thresholds. |
|||
* It is assumed that the given polytope contains the downward closure of its vertices. |
|||
*/ |
|||
bool checkIfThresholdsAreSatisfied(std::shared_ptr<storm::storage::geometry::Polytope<GeometryValueType>> const& polytope); |
|||
|
|||
|
|||
Point thresholds; |
|||
storm::storage::BitVector strictThresholds; |
|||
}; |
|||
|
|||
} |
|||
} |
|||
} |
|||
|
|||
#endif /* STORM_MODELCHECKER_MULTIOBJECTIVE_PCAA_SPARSEPCAAACHIEVABILITYQUERY_H_ */ |
@ -0,0 +1,101 @@ |
|||
#include "src/modelchecker/multiobjective/pcaa/SparsePcaaParetoQuery.h"
|
|||
|
|||
#include "src/adapters/CarlAdapter.h"
|
|||
#include "src/models/sparse/Mdp.h"
|
|||
#include "src/models/sparse/MarkovAutomaton.h"
|
|||
#include "src/models/sparse/StandardRewardModel.h"
|
|||
#include "src/modelchecker/results/ParetoCurveCheckResult.h"
|
|||
#include "src/utility/constants.h"
|
|||
#include "src/utility/vector.h"
|
|||
#include "src/settings//SettingsManager.h"
|
|||
#include "src/settings/modules/MultiObjectiveSettings.h"
|
|||
#include "src/settings/modules/GeneralSettings.h"
|
|||
|
|||
|
|||
namespace storm { |
|||
namespace modelchecker { |
|||
namespace multiobjective { |
|||
|
|||
template <class SparseModelType, typename GeometryValueType> |
|||
SparsePcaaParetoQuery<SparseModelType, GeometryValueType>::SparsePcaaParetoQuery(SparsePcaaPreprocessorReturnType<SparseModelType>& preprocessorResult) : SparsePcaaQuery<SparseModelType, GeometryValueType>(preprocessorResult) { |
|||
STORM_LOG_ASSERT(preprocessorResult.queryType==SparsePcaaPreprocessorReturnType<SparseModelType>::QueryType::Pareto, "Invalid query Type"); |
|||
|
|||
// Set the maximum gap between lower and upper bound of the weightVectorChecker result.
|
|||
// This is the maximal edge length of the box we have to consider around each computed point
|
|||
// We pick the gap such that the maximal distance between two points within this box is less than the given precision divided by two.
|
|||
typename SparseModelType::ValueType gap = storm::utility::convertNumber<typename SparseModelType::ValueType>(storm::settings::getModule<storm::settings::modules::MultiObjectiveSettings>().getPrecision()); |
|||
gap /= (storm::utility::one<typename SparseModelType::ValueType>() + storm::utility::one<typename SparseModelType::ValueType>()); |
|||
gap /= storm::utility::sqrt(static_cast<typename SparseModelType::ValueType>(this->objectives.size())); |
|||
this->weightVectorChecker->setMaximumLowerUpperBoundGap(gap); |
|||
|
|||
} |
|||
|
|||
template <class SparseModelType, typename GeometryValueType> |
|||
std::unique_ptr<CheckResult> SparsePcaaParetoQuery<SparseModelType, GeometryValueType>::check() { |
|||
|
|||
// refine the approximation
|
|||
exploreSetOfAchievablePoints(); |
|||
|
|||
// obtain the data for the checkresult
|
|||
std::vector<std::vector<typename SparseModelType::ValueType>> paretoOptimalPoints; |
|||
paretoOptimalPoints.reserve(this->refinementSteps.size()); |
|||
for(auto const& step : this->refinementSteps) { |
|||
paretoOptimalPoints.push_back(storm::utility::vector::convertNumericVector<typename SparseModelType::ValueType>(this->transformPointToOriginalModel(step.lowerBoundPoint))); |
|||
} |
|||
return std::unique_ptr<CheckResult>(new ParetoCurveCheckResult<typename SparseModelType::ValueType>(this->originalModel.getInitialStates().getNextSetIndex(0), |
|||
std::move(paretoOptimalPoints), |
|||
this->transformPolytopeToOriginalModel(this->underApproximation)->template convertNumberRepresentation<typename SparseModelType::ValueType>(), |
|||
this->transformPolytopeToOriginalModel(this->overApproximation)->template convertNumberRepresentation<typename SparseModelType::ValueType>())); |
|||
|
|||
|
|||
} |
|||
|
|||
template <class SparseModelType, typename GeometryValueType> |
|||
void SparsePcaaParetoQuery<SparseModelType, GeometryValueType>::exploreSetOfAchievablePoints() { |
|||
|
|||
//First consider the objectives individually
|
|||
for(uint_fast64_t objIndex = 0; objIndex<this->objectives.size() && !this->maxStepsPerformed(); ++objIndex) { |
|||
WeightVector direction(this->objectives.size(), storm::utility::zero<GeometryValueType>()); |
|||
direction[objIndex] = storm::utility::one<GeometryValueType>(); |
|||
this->performRefinementStep(std::move(direction)); |
|||
} |
|||
|
|||
while(!this->maxStepsPerformed()) { |
|||
// Get the halfspace of the underApproximation with maximal distance to a vertex of the overApproximation
|
|||
std::vector<storm::storage::geometry::Halfspace<GeometryValueType>> underApproxHalfspaces = this->underApproximation->getHalfspaces(); |
|||
std::vector<Point> overApproxVertices = this->overApproximation->getVertices(); |
|||
uint_fast64_t farestHalfspaceIndex = underApproxHalfspaces.size(); |
|||
GeometryValueType farestDistance = storm::utility::zero<GeometryValueType>(); |
|||
for(uint_fast64_t halfspaceIndex = 0; halfspaceIndex < underApproxHalfspaces.size(); ++halfspaceIndex) { |
|||
for(auto const& vertex : overApproxVertices) { |
|||
GeometryValueType distance = -underApproxHalfspaces[halfspaceIndex].euclideanDistance(vertex); |
|||
if(distance > farestDistance) { |
|||
farestHalfspaceIndex = halfspaceIndex; |
|||
farestDistance = distance; |
|||
} |
|||
} |
|||
} |
|||
if(farestDistance < storm::utility::convertNumber<GeometryValueType>(storm::settings::getModule<storm::settings::modules::MultiObjectiveSettings>().getPrecision())) { |
|||
// Goal precision reached!
|
|||
return; |
|||
} |
|||
STORM_LOG_DEBUG("Current precision of the approximation of the pareto curve is ~" << storm::utility::convertNumber<double>(farestDistance)); |
|||
WeightVector direction = underApproxHalfspaces[farestHalfspaceIndex].normalVector(); |
|||
this->performRefinementStep(std::move(direction)); |
|||
} |
|||
STORM_LOG_ERROR("Could not reach the desired precision: Exceeded maximum number of refinement steps"); |
|||
} |
|||
|
|||
|
|||
|
|||
|
|||
#ifdef STORM_HAVE_CARL
|
|||
template class SparsePcaaParetoQuery<storm::models::sparse::Mdp<double>, storm::RationalNumber>; |
|||
template class SparsePcaaParetoQuery<storm::models::sparse::MarkovAutomaton<double>, storm::RationalNumber>; |
|||
|
|||
template class SparsePcaaParetoQuery<storm::models::sparse::Mdp<storm::RationalNumber>, storm::RationalNumber>; |
|||
// template class SparsePcaaParetoQuery<storm::models::sparse::MarkovAutomaton<storm::RationalNumber>, storm::RationalNumber>;
|
|||
#endif
|
|||
} |
|||
} |
|||
} |
@ -0,0 +1,47 @@ |
|||
#ifndef STORM_MODELCHECKER_MULTIOBJECTIVE_PCAA_SPARSEPCAAPARETOQUERY_H_ |
|||
#define STORM_MODELCHECKER_MULTIOBJECTIVE_PCAA_SPARSEPCAAPARETOQUERY_H_ |
|||
|
|||
#include "src/modelchecker/multiobjective/pcaa/SparsePcaaQuery.h" |
|||
|
|||
namespace storm { |
|||
namespace modelchecker { |
|||
namespace multiobjective { |
|||
|
|||
/* |
|||
* This class represents a query for the Pareto curve approximation algorithm (Pcaa). |
|||
* It implements the necessary computations for the different query types. |
|||
*/ |
|||
template <class SparseModelType, typename GeometryValueType> |
|||
class SparsePcaaParetoQuery : public SparsePcaaQuery<SparseModelType, GeometryValueType> { |
|||
public: |
|||
|
|||
// Typedefs for simple geometric objects |
|||
typedef std::vector<GeometryValueType> Point; |
|||
typedef std::vector<GeometryValueType> WeightVector; |
|||
|
|||
/* |
|||
* Creates a new query for the Pareto curve approximation algorithm (Pcaa) |
|||
* @param preprocessorResult the result from preprocessing |
|||
*/ |
|||
SparsePcaaParetoQuery(SparsePcaaPreprocessorReturnType<SparseModelType>& preprocessorResult); |
|||
|
|||
|
|||
/* |
|||
* Invokes the computation and retrieves the result |
|||
*/ |
|||
virtual std::unique_ptr<CheckResult> check() override; |
|||
|
|||
private: |
|||
|
|||
|
|||
/* |
|||
* Performs refinement steps until the approximation is sufficiently precise |
|||
*/ |
|||
void exploreSetOfAchievablePoints(); |
|||
}; |
|||
|
|||
} |
|||
} |
|||
} |
|||
|
|||
#endif /* STORM_MODELCHECKER_MULTIOBJECTIVE_PCAA_SPARSEPCAAPARETOQUERY_H_ */ |
Write
Preview
Loading…
Cancel
Save
Reference in new issue