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The variable pool of carl needs to be cleared after executing a test. 

Sampling for mdps now uses the policy of the previous iteration as initial guess


Former-commit-id: 3b8b25f30f
main
TimQu 10 years ago
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358bc14ded
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bf450688b4
5 changed files with 41 additions and 31 deletions
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  1. 7
      src/modelchecker/region/ApproximationModel.cpp
  2. 24
      src/modelchecker/region/SamplingModel.cpp
  3. 24
      src/modelchecker/region/SamplingModel.h
  4. 9
      test/functional/modelchecker/SparseDtmcRegionModelCheckerTest.cpp
  5. 8
      test/functional/modelchecker/SparseMdpRegionModelCheckerTest.cpp

7
src/modelchecker/region/ApproximationModel.cpp
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@ -70,6 +70,9 @@ namespace storm {
this->solverData.result = std::vector<ConstantType>(maybeStates.getNumberOfSetBits(), this->computeRewards ? storm::utility::one<ConstantType>() : ConstantType(0.5));
this->solverData.initialStateIndex = newIndices[initialState];
this->solverData.lastMinimizingPolicy = Policy(this->matrixData.matrix.getRowGroupCount(), 0);
this->solverData.lastMaximizingPolicy = Policy(this->matrixData.matrix.getRowGroupCount(), 0);
this->solverData.lastPlayer1Policy = Policy(this->matrixData.matrix.getRowGroupCount(), 0);
}
template<typename ParametricSparseModelType, typename ConstantType>
@ -272,10 +275,6 @@ namespace storm {
instantiate(region, computeLowerBounds);
Policy& policy = computeLowerBounds ? this->solverData.lastMinimizingPolicy : this->solverData.lastMaximizingPolicy;
//TODO: at this point, set policy to the one stored in the region.
if(policy.empty()){
//No guess available (yet)
policy = Policy(this->matrixData.matrix.getRowGroupCount(), 0);
}
invokeSolver(computeLowerBounds, policy);
//TODO: policy for games.

24
src/modelchecker/region/SamplingModel.cpp
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@ -26,7 +26,7 @@ namespace storm {
namespace region {
template<typename ParametricSparseModelType, typename ConstantType>
SamplingModel<ParametricSparseModelType, ConstantType>::SamplingModel(ParametricSparseModelType const& parametricModel, std::shared_ptr<storm::logic::OperatorFormula> formula) : solveGoal(storm::logic::isLowerBound(formula->getComparisonType())){
SamplingModel<ParametricSparseModelType, ConstantType>::SamplingModel(ParametricSparseModelType const& parametricModel, std::shared_ptr<storm::logic::OperatorFormula> formula){
//First some simple checks and initializations..
if(formula->isProbabilityOperatorFormula()){
this->computeRewards=false;
@ -38,6 +38,7 @@ namespace storm {
} else {
STORM_LOG_THROW(false, storm::exceptions::InvalidArgumentException, "Invalid formula: " << formula << ". Sampling model only supports eventually or reachability reward formulae.");
}
this->solverData.solveGoal = storm::solver::SolveGoal(storm::logic::isLowerBound(formula->getComparisonType()));
STORM_LOG_THROW(parametricModel.hasLabel("target"), storm::exceptions::InvalidArgumentException, "The given Model has no \"target\"-statelabel.");
this->targetStates = parametricModel.getStateLabeling().getStates("target");
STORM_LOG_THROW(parametricModel.hasLabel("sink"), storm::exceptions::InvalidArgumentException, "The given Model has no \"sink\"-statelabel.");
@ -63,8 +64,9 @@ namespace storm {
this->matrixData.assignment.shrink_to_fit();
this->vectorData.assignment.shrink_to_fit();
this->eqSysResult = std::vector<ConstantType>(maybeStates.getNumberOfSetBits(), this->computeRewards ? storm::utility::one<ConstantType>() : ConstantType(0.5));
this->eqSysInitIndex = newIndices[initialState];
this->solverData.result = std::vector<ConstantType>(maybeStates.getNumberOfSetBits(), this->computeRewards ? storm::utility::one<ConstantType>() : ConstantType(0.5));
this->solverData.initialStateIndex = newIndices[initialState];
this->solverData.lastPolicy = Policy(this->matrixData.matrix.getRowGroupCount(), 0);
}
template<typename ParametricSparseModelType, typename ConstantType>
@ -209,7 +211,7 @@ namespace storm {
instantiate(point);
invokeSolver();
std::vector<ConstantType> result(this->maybeStates.size());
storm::utility::vector::setVectorValues(result, this->maybeStates, this->eqSysResult);
storm::utility::vector::setVectorValues(result, this->maybeStates, this->solverData.result);
storm::utility::vector::setVectorValues(result, this->targetStates, this->computeRewards ? storm::utility::zero<ConstantType>() : storm::utility::one<ConstantType>());
storm::utility::vector::setVectorValues(result, ~(this->maybeStates | this->targetStates), this->computeRewards ? storm::utility::infinity<ConstantType>() : storm::utility::zero<ConstantType>());
@ -220,7 +222,7 @@ namespace storm {
ConstantType SamplingModel<ParametricSparseModelType, ConstantType>::computeInitialStateValue(std::map<VariableType, CoefficientType>const& point) {
instantiate(point);
invokeSolver();
return this->eqSysResult[this->eqSysInitIndex];
return this->solverData.result[this->solverData.initialStateIndex];
}
template<typename ParametricSparseModelType, typename ConstantType>
@ -247,16 +249,14 @@ namespace storm {
template<>
void SamplingModel<storm::models::sparse::Dtmc<storm::RationalFunction>, double>::invokeSolver(){
std::unique_ptr<storm::solver::LinearEquationSolver<double>> solver = storm::utility::solver::LinearEquationSolverFactory<double>().create(this->matrixData.matrix);
solver->solveEquationSystem(this->eqSysResult, this->vectorData.vector);
solver->solveEquationSystem(this->solverData.result, this->vectorData.vector);
}
template<>
void SamplingModel<storm::models::sparse::Mdp<storm::RationalFunction>, double>::invokeSolver(){
std::unique_ptr<storm::solver::MinMaxLinearEquationSolver<double>> solver = storm::solver::configureMinMaxLinearEquationSolver(this->solveGoal, storm::utility::solver::MinMaxLinearEquationSolverFactory<double>(), this->matrixData.matrix);
if(!this->solveGoal.minimize()){
//The value iteration method is not correct if the value is maximized and the initial x-vector is not <= the actual probability/reward.
this->eqSysResult.assign(this->eqSysResult.size(), storm::utility::zero<double>());
}
solver->solveEquationSystem(this->eqSysResult, this->vectorData.vector);
std::unique_ptr<storm::solver::MinMaxLinearEquationSolver<double>> solver = storm::solver::configureMinMaxLinearEquationSolver(this->solverData.solveGoal, storm::utility::solver::MinMaxLinearEquationSolverFactory<double>(), this->matrixData.matrix);
solver->setPolicyTracking();
solver->solveEquationSystem(this->solverData.solveGoal.direction(), this->solverData.result, this->vectorData.vector, nullptr, nullptr, &this->solverData.lastPolicy);
this->solverData.lastPolicy = solver->getPolicy();
}

24
src/modelchecker/region/SamplingModel.h
View File

@ -51,24 +51,28 @@ namespace storm {
ConstantType computeInitialStateValue(std::map<VariableType, CoefficientType>const& point);
private:
typedef typename std::unordered_map<ParametricType, ConstantType>::value_type FunctionEntry;
typedef std::vector<storm::storage::sparse::state_type> Policy;
void initializeProbabilities(ParametricSparseModelType const& parametricModel, std::vector<std::size_t> const& newIndices);
void initializeRewards(ParametricSparseModelType const& parametricModel, std::vector<std::size_t> const& newIndices);
void instantiate(std::map<VariableType, CoefficientType>const& point);
void invokeSolver();
//Some designated states in the original model
storm::storage::BitVector targetStates, maybeStates;
//The last result of the solving the equation system. Also serves as first guess for the next call.
//Note: eqSysResult.size==maybeStates.numberOfSetBits
std::vector<ConstantType> eqSysResult;
//The index which represents the result for the initial state in the eqSysResult vector
std::size_t eqSysInitIndex;
//A flag that denotes whether we compute probabilities or rewards
bool computeRewards;
//The goal we want to accomplish when solving the eq sys.
storm::solver::SolveGoal solveGoal;
//Some designated states in the original model
storm::storage::BitVector targetStates, maybeStates;
struct SolverData{
//The result from the previous instantiation. Serve as first guess for the next call.
std::vector<ConstantType> result; //Note: result.size==maybeStates.numberOfSetBits
std::size_t initialStateIndex; //The index which represents the result for the initial state in the result vector
//The following is only relevant if we consider mdps:
storm::solver::SolveGoal solveGoal = storm::solver::SolveGoal(true); //No default cunstructor for solve goal...
Policy lastPolicy; //best policy from the previous instantiation. Serves as first guess for the next call.
} solverData;
/* The data required for the equation system, i.e., a matrix and a vector.

9
test/functional/modelchecker/SparseDtmcRegionModelCheckerTest.cpp
View File

@ -87,10 +87,10 @@ TEST(SparseDtmcRegionModelCheckerTest, Brp_Prob) {
//smt EXPECT_EQ((storm::modelchecker::region::RegionCheckResult::ALLVIOLATED), allVioRegionSmt.getCheckResult());
storm::settings::mutableRegionSettings().resetModes();
carl::VariablePool::getInstance().clear();
}
TEST(SparseDtmcRegionModelCheckerTest, Brp_Rew) {
std::string const& programFile = STORM_CPP_BASE_PATH "/examples/pdtmc/brp_rewards/brp_16_2.pm";
std::string const& formulaAsString = "R>2.5 [F \"target\" ]";
std::string const& constantsAsString = "pL=0.9,TOAck=0.5";
@ -178,8 +178,8 @@ TEST(SparseDtmcRegionModelCheckerTest, Brp_Rew) {
modelchecker.checkRegion(exBothHardRegionSmt);
//smt EXPECT_EQ((storm::modelchecker::region::RegionCheckResult::EXISTSBOTH), exBothHardRegionSmtApp.getCheckResult());
storm::settings::mutableRegionSettings().resetModes();
carl::VariablePool::getInstance().clear();
}
TEST(SparseDtmcRegionModelCheckerTest, Brp_Rew_Infty) {
@ -226,6 +226,7 @@ TEST(SparseDtmcRegionModelCheckerTest, Brp_Rew_Infty) {
//smt EXPECT_EQ((storm::modelchecker::region::RegionCheckResult::ALLSAT), allSatRegionSmt.getCheckResult());
storm::settings::mutableRegionSettings().resetModes();
carl::VariablePool::getInstance().clear();
}
TEST(SparseDtmcRegionModelCheckerTest, Brp_Rew_4Par) {
@ -289,6 +290,7 @@ TEST(SparseDtmcRegionModelCheckerTest, Brp_Rew_4Par) {
//smt EXPECT_EQ((storm::modelchecker::region::RegionCheckResult::ALLVIOLATED), allVioRegionSmt.getCheckResult());
storm::settings::mutableRegionSettings().resetModes();
carl::VariablePool::getInstance().clear();
}
TEST(SparseDtmcRegionModelCheckerTest, Crowds_Prob) {
@ -377,6 +379,7 @@ TEST(SparseDtmcRegionModelCheckerTest, Crowds_Prob) {
//smt EXPECT_EQ((storm::modelchecker::region::RegionCheckResult::ALLVIOLATED), allVioHardRegionSmtApp.getCheckResult());
storm::settings::mutableRegionSettings().resetModes();
carl::VariablePool::getInstance().clear();
}
TEST(SparseDtmcRegionModelCheckerTest, Crowds_Prob_1Par) {
@ -442,6 +445,7 @@ TEST(SparseDtmcRegionModelCheckerTest, Crowds_Prob_1Par) {
//smt EXPECT_EQ((storm::modelchecker::region::RegionCheckResult::ALLVIOLATED), allVioRegionSmt.getCheckResult());
storm::settings::mutableRegionSettings().resetModes();
carl::VariablePool::getInstance().clear();
}
TEST(SparseDtmcRegionModelCheckerTest, Crowds_Prob_Const) {
@ -490,6 +494,7 @@ TEST(SparseDtmcRegionModelCheckerTest, Crowds_Prob_Const) {
//smt EXPECT_EQ((storm::modelchecker::region::RegionCheckResult::ALLSAT), allSatRegionSmt.getCheckResult());
storm::settings::mutableRegionSettings().resetModes();
carl::VariablePool::getInstance().clear();
}
#endif

8
test/functional/modelchecker/SparseMdpRegionModelCheckerTest.cpp
View File

@ -66,6 +66,7 @@ TEST(SparseMdpRegionModelCheckerTest, two_dice_Prob) {
EXPECT_EQ((storm::modelchecker::region::RegionCheckResult::ALLVIOLATED), allVioRegion.getCheckResult());
storm::settings::mutableRegionSettings().resetModes();
carl::VariablePool::getInstance().clear();
}
TEST(SparseMdpRegionModelCheckerTest, coin_Prob) {
@ -94,11 +95,11 @@ TEST(SparseMdpRegionModelCheckerTest, coin_Prob) {
auto exBothRegion=storm::modelchecker::region::ParameterRegion<storm::RationalFunction>::parseRegion("0.4<=p<=0.65,0.5<=q<=0.7");
auto allVioRegion=storm::modelchecker::region::ParameterRegion<storm::RationalFunction>::parseRegion("0.4<=p<=0.7,0.55<=q<=0.6");
EXPECT_NEAR(0.9512773402, modelchecker.getReachabilityValue(allSatRegion.getLowerBounds()), storm::settings::generalSettings().getPrecision());
EXPECT_NEAR(0.95127874851, modelchecker.getReachabilityValue(allSatRegion.getLowerBounds()), storm::settings::generalSettings().getPrecision());
EXPECT_NEAR(0.26787251126, modelchecker.getReachabilityValue(allSatRegion.getUpperBounds()), storm::settings::generalSettings().getPrecision());
EXPECT_NEAR(0.41879628383, modelchecker.getReachabilityValue(exBothRegion.getLowerBounds()), storm::settings::generalSettings().getPrecision());
EXPECT_NEAR(0.41880006098, modelchecker.getReachabilityValue(exBothRegion.getLowerBounds()), storm::settings::generalSettings().getPrecision());
EXPECT_NEAR(0.01535089684, modelchecker.getReachabilityValue(exBothRegion.getUpperBounds()), storm::settings::generalSettings().getPrecision());
EXPECT_NEAR(0.24952471590, modelchecker.getReachabilityValue(allVioRegion.getLowerBounds()), storm::settings::generalSettings().getPrecision());
EXPECT_NEAR(0.24952791523, modelchecker.getReachabilityValue(allVioRegion.getLowerBounds()), storm::settings::generalSettings().getPrecision());
EXPECT_NEAR(0.01711494956, modelchecker.getReachabilityValue(allVioRegion.getUpperBounds()), storm::settings::generalSettings().getPrecision());
//test approximative method
@ -114,6 +115,7 @@ TEST(SparseMdpRegionModelCheckerTest, coin_Prob) {
EXPECT_EQ((storm::modelchecker::region::RegionCheckResult::ALLVIOLATED), allVioRegion.getCheckResult());
storm::settings::mutableRegionSettings().resetModes();
carl::VariablePool::getInstance().clear();
}
#endif
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