You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
196 lines
14 KiB
196 lines
14 KiB
#include "gtest/gtest.h"
|
|
#include "storm-config.h"
|
|
|
|
#include "src/logic/Formulas.h"
|
|
#include "src/utility/solver.h"
|
|
#include "src/modelchecker/prctl/SparseMdpPrctlModelChecker.h"
|
|
#include "src/modelchecker/results/ExplicitQuantitativeCheckResult.h"
|
|
#include "src/settings/SettingsManager.h"
|
|
#include "src/parser/AutoParser.h"
|
|
|
|
TEST(GmmxxMdpPrctlModelCheckerTest, Dice) {
|
|
std::shared_ptr<storm::models::sparse::Model<double>> abstractModel = storm::parser::AutoParser::parseModel(STORM_CPP_BASE_PATH "/examples/mdp/two_dice/two_dice.tra", STORM_CPP_BASE_PATH "/examples/mdp/two_dice/two_dice.lab", "", STORM_CPP_BASE_PATH "/examples/mdp/two_dice/two_dice.flip.trans.rew");
|
|
|
|
ASSERT_EQ(abstractModel->getType(), storm::models::ModelType::Mdp);
|
|
|
|
std::shared_ptr<storm::models::sparse::Mdp<double>> mdp = abstractModel->as<storm::models::sparse::Mdp<double>>();
|
|
|
|
ASSERT_EQ(mdp->getNumberOfStates(), 169ull);
|
|
ASSERT_EQ(mdp->getNumberOfTransitions(), 436ull);
|
|
|
|
storm::modelchecker::SparseMdpPrctlModelChecker<double> checker(*mdp, std::unique_ptr<storm::utility::solver::MinMaxLinearEquationSolverFactory<double>>(new storm::utility::solver::GmmxxMinMaxLinearEquationSolverFactory<double>()));
|
|
|
|
auto labelFormula = std::make_shared<storm::logic::AtomicLabelFormula>("two");
|
|
auto eventuallyFormula = std::make_shared<storm::logic::EventuallyFormula>(labelFormula);
|
|
auto minProbabilityOperatorFormula = std::make_shared<storm::logic::ProbabilityOperatorFormula>(storm::logic::OptimalityType::Minimize, eventuallyFormula);
|
|
|
|
std::unique_ptr<storm::modelchecker::CheckResult> result = checker.check(*minProbabilityOperatorFormula);
|
|
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeResult1 = result->asExplicitQuantitativeCheckResult<double>();
|
|
|
|
EXPECT_NEAR(0.0277777612209320068, quantitativeResult1[0], storm::settings::nativeEquationSolverSettings().getPrecision());
|
|
|
|
auto maxProbabilityOperatorFormula = std::make_shared<storm::logic::ProbabilityOperatorFormula>(storm::logic::OptimalityType::Maximize, eventuallyFormula);
|
|
|
|
result = checker.check(*maxProbabilityOperatorFormula);
|
|
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeResult2 = result->asExplicitQuantitativeCheckResult<double>();
|
|
|
|
EXPECT_NEAR(0.0277777612209320068, quantitativeResult2[0], storm::settings::nativeEquationSolverSettings().getPrecision());
|
|
|
|
labelFormula = std::make_shared<storm::logic::AtomicLabelFormula>("three");
|
|
eventuallyFormula = std::make_shared<storm::logic::EventuallyFormula>(labelFormula);
|
|
minProbabilityOperatorFormula = std::make_shared<storm::logic::ProbabilityOperatorFormula>(storm::logic::OptimalityType::Minimize, eventuallyFormula);
|
|
|
|
result = checker.check(*minProbabilityOperatorFormula);
|
|
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeResult3 = result->asExplicitQuantitativeCheckResult<double>();
|
|
|
|
EXPECT_NEAR(0.0555555224418640136, quantitativeResult3[0], storm::settings::nativeEquationSolverSettings().getPrecision());
|
|
|
|
maxProbabilityOperatorFormula = std::make_shared<storm::logic::ProbabilityOperatorFormula>(storm::logic::OptimalityType::Maximize, eventuallyFormula);
|
|
|
|
result = checker.check(*maxProbabilityOperatorFormula);
|
|
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeResult4 = result->asExplicitQuantitativeCheckResult<double>();
|
|
|
|
EXPECT_NEAR(0.0555555224418640136, quantitativeResult4[0], storm::settings::nativeEquationSolverSettings().getPrecision());
|
|
|
|
labelFormula = std::make_shared<storm::logic::AtomicLabelFormula>("four");
|
|
eventuallyFormula = std::make_shared<storm::logic::EventuallyFormula>(labelFormula);
|
|
minProbabilityOperatorFormula = std::make_shared<storm::logic::ProbabilityOperatorFormula>(storm::logic::OptimalityType::Minimize, eventuallyFormula);
|
|
|
|
result = checker.check(*minProbabilityOperatorFormula);
|
|
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeResult5 = result->asExplicitQuantitativeCheckResult<double>();
|
|
|
|
EXPECT_NEAR(0.083333283662796020508, quantitativeResult5[0], storm::settings::nativeEquationSolverSettings().getPrecision());
|
|
|
|
maxProbabilityOperatorFormula = std::make_shared<storm::logic::ProbabilityOperatorFormula>(storm::logic::OptimalityType::Maximize, eventuallyFormula);
|
|
|
|
result = checker.check(*maxProbabilityOperatorFormula);
|
|
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeResult6 = result->asExplicitQuantitativeCheckResult<double>();
|
|
|
|
EXPECT_NEAR(0.083333283662796020508, quantitativeResult6[0], storm::settings::nativeEquationSolverSettings().getPrecision());
|
|
|
|
labelFormula = std::make_shared<storm::logic::AtomicLabelFormula>("done");
|
|
auto reachabilityRewardFormula = std::make_shared<storm::logic::ReachabilityRewardFormula>(labelFormula);
|
|
auto minRewardOperatorFormula = std::make_shared<storm::logic::RewardOperatorFormula>(storm::logic::OptimalityType::Minimize, reachabilityRewardFormula);
|
|
|
|
result = checker.check(*minRewardOperatorFormula);
|
|
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeResult7 = result->asExplicitQuantitativeCheckResult<double>();
|
|
|
|
EXPECT_NEAR(7.333329499, quantitativeResult7[0], storm::settings::nativeEquationSolverSettings().getPrecision());
|
|
|
|
auto maxRewardOperatorFormula = std::make_shared<storm::logic::RewardOperatorFormula>(storm::logic::OptimalityType::Maximize, reachabilityRewardFormula);
|
|
|
|
result = checker.check(*maxRewardOperatorFormula);
|
|
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeResult8 = result->asExplicitQuantitativeCheckResult<double>();
|
|
|
|
EXPECT_NEAR(7.333329499, quantitativeResult8[0], storm::settings::nativeEquationSolverSettings().getPrecision());
|
|
|
|
abstractModel = storm::parser::AutoParser::parseModel(STORM_CPP_BASE_PATH "/examples/mdp/two_dice/two_dice.tra", STORM_CPP_BASE_PATH "/examples/mdp/two_dice/two_dice.lab", STORM_CPP_BASE_PATH "/examples/mdp/two_dice/two_dice.flip.state.rew", "");
|
|
|
|
ASSERT_EQ(abstractModel->getType(), storm::models::ModelType::Mdp);
|
|
|
|
std::shared_ptr<storm::models::sparse::Mdp<double>> stateRewardMdp = abstractModel->as<storm::models::sparse::Mdp<double>>();
|
|
|
|
storm::modelchecker::SparseMdpPrctlModelChecker<double> stateRewardModelChecker(*mdp, std::unique_ptr<storm::utility::solver::MinMaxLinearEquationSolverFactory<double>>(new storm::utility::solver::GmmxxMinMaxLinearEquationSolverFactory<double>()));
|
|
|
|
labelFormula = std::make_shared<storm::logic::AtomicLabelFormula>("done");
|
|
reachabilityRewardFormula = std::make_shared<storm::logic::ReachabilityRewardFormula>(labelFormula);
|
|
minRewardOperatorFormula = std::make_shared<storm::logic::RewardOperatorFormula>(storm::logic::OptimalityType::Minimize, reachabilityRewardFormula);
|
|
|
|
result = stateRewardModelChecker.check(*minRewardOperatorFormula);
|
|
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeResult9 = result->asExplicitQuantitativeCheckResult<double>();
|
|
|
|
EXPECT_NEAR(7.333329499, quantitativeResult9[0], storm::settings::nativeEquationSolverSettings().getPrecision());
|
|
|
|
maxRewardOperatorFormula = std::make_shared<storm::logic::RewardOperatorFormula>(storm::logic::OptimalityType::Maximize, reachabilityRewardFormula);
|
|
|
|
result = stateRewardModelChecker.check(*maxRewardOperatorFormula);
|
|
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeResult10 = result->asExplicitQuantitativeCheckResult<double>();
|
|
|
|
EXPECT_NEAR(7.333329499, quantitativeResult10[0], storm::settings::nativeEquationSolverSettings().getPrecision());
|
|
|
|
abstractModel = storm::parser::AutoParser::parseModel(STORM_CPP_BASE_PATH "/examples/mdp/two_dice/two_dice.tra", STORM_CPP_BASE_PATH "/examples/mdp/two_dice/two_dice.lab", STORM_CPP_BASE_PATH "/examples/mdp/two_dice/two_dice.flip.state.rew", STORM_CPP_BASE_PATH "/examples/mdp/two_dice/two_dice.flip.trans.rew");
|
|
|
|
ASSERT_EQ(abstractModel->getType(), storm::models::ModelType::Mdp);
|
|
|
|
std::shared_ptr<storm::models::sparse::Mdp<double>> stateAndTransitionRewardMdp = abstractModel->as<storm::models::sparse::Mdp<double>>();
|
|
|
|
storm::modelchecker::SparseMdpPrctlModelChecker<double> stateAndTransitionRewardModelChecker(*stateAndTransitionRewardMdp, std::unique_ptr<storm::utility::solver::MinMaxLinearEquationSolverFactory<double>>(new storm::utility::solver::GmmxxMinMaxLinearEquationSolverFactory<double>()));
|
|
|
|
labelFormula = std::make_shared<storm::logic::AtomicLabelFormula>("done");
|
|
reachabilityRewardFormula = std::make_shared<storm::logic::ReachabilityRewardFormula>(labelFormula);
|
|
minRewardOperatorFormula = std::make_shared<storm::logic::RewardOperatorFormula>(storm::logic::OptimalityType::Minimize, reachabilityRewardFormula);
|
|
|
|
result = stateAndTransitionRewardModelChecker.check(*minRewardOperatorFormula);
|
|
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeResult11 = result->asExplicitQuantitativeCheckResult<double>();
|
|
|
|
EXPECT_NEAR(14.666658998, quantitativeResult11[0], storm::settings::nativeEquationSolverSettings().getPrecision());
|
|
|
|
maxRewardOperatorFormula = std::make_shared<storm::logic::RewardOperatorFormula>(storm::logic::OptimalityType::Maximize, reachabilityRewardFormula);
|
|
|
|
result = stateAndTransitionRewardModelChecker.check(*maxRewardOperatorFormula);
|
|
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeResult12 = result->asExplicitQuantitativeCheckResult<double>();
|
|
|
|
EXPECT_NEAR(14.666658998, quantitativeResult12[0], storm::settings::nativeEquationSolverSettings().getPrecision());
|
|
}
|
|
|
|
TEST(GmmxxMdpPrctlModelCheckerTest, AsynchronousLeader) {
|
|
std::shared_ptr<storm::models::sparse::Model<double>> abstractModel = storm::parser::AutoParser::parseModel(STORM_CPP_BASE_PATH "/examples/mdp/asynchronous_leader/leader4.tra", STORM_CPP_BASE_PATH "/examples/mdp/asynchronous_leader/leader4.lab", "", STORM_CPP_BASE_PATH "/examples/mdp/asynchronous_leader/leader4.trans.rew");
|
|
|
|
ASSERT_EQ(storm::models::ModelType::Mdp, abstractModel->getType());
|
|
|
|
std::shared_ptr<storm::models::sparse::Mdp<double>> mdp = abstractModel->as<storm::models::sparse::Mdp<double>>();
|
|
|
|
ASSERT_EQ(3172ull, mdp->getNumberOfStates());
|
|
ASSERT_EQ(7144ull, mdp->getNumberOfTransitions());
|
|
|
|
storm::modelchecker::SparseMdpPrctlModelChecker<double> checker(*mdp, std::unique_ptr<storm::utility::solver::MinMaxLinearEquationSolverFactory<double>>(new storm::utility::solver::GmmxxMinMaxLinearEquationSolverFactory<double>()));
|
|
|
|
auto labelFormula = std::make_shared<storm::logic::AtomicLabelFormula>("elected");
|
|
auto eventuallyFormula = std::make_shared<storm::logic::EventuallyFormula>(labelFormula);
|
|
auto minProbabilityOperatorFormula = std::make_shared<storm::logic::ProbabilityOperatorFormula>(storm::logic::OptimalityType::Minimize, eventuallyFormula);
|
|
|
|
std::unique_ptr<storm::modelchecker::CheckResult> result = checker.check(*minProbabilityOperatorFormula);
|
|
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeResult1 = result->asExplicitQuantitativeCheckResult<double>();
|
|
|
|
EXPECT_NEAR(1, quantitativeResult1[0], storm::settings::nativeEquationSolverSettings().getPrecision());
|
|
|
|
auto maxProbabilityOperatorFormula = std::make_shared<storm::logic::ProbabilityOperatorFormula>(storm::logic::OptimalityType::Maximize, eventuallyFormula);
|
|
|
|
result = checker.check(*maxProbabilityOperatorFormula);
|
|
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeResult2 = result->asExplicitQuantitativeCheckResult<double>();
|
|
|
|
EXPECT_NEAR(1, quantitativeResult2[0], storm::settings::nativeEquationSolverSettings().getPrecision());
|
|
|
|
labelFormula = std::make_shared<storm::logic::AtomicLabelFormula>("elected");
|
|
auto trueFormula = std::make_shared<storm::logic::BooleanLiteralFormula>(true);
|
|
auto boundedUntilFormula = std::make_shared<storm::logic::BoundedUntilFormula>(trueFormula, labelFormula, 25);
|
|
minProbabilityOperatorFormula = std::make_shared<storm::logic::ProbabilityOperatorFormula>(storm::logic::OptimalityType::Minimize, boundedUntilFormula);
|
|
|
|
result = checker.check(*minProbabilityOperatorFormula);
|
|
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeResult3 = result->asExplicitQuantitativeCheckResult<double>();
|
|
|
|
EXPECT_NEAR(0.0625, quantitativeResult3[0], storm::settings::nativeEquationSolverSettings().getPrecision());
|
|
|
|
maxProbabilityOperatorFormula = std::make_shared<storm::logic::ProbabilityOperatorFormula>(storm::logic::OptimalityType::Maximize, boundedUntilFormula);
|
|
|
|
result = checker.check(*maxProbabilityOperatorFormula);
|
|
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeResult4 = result->asExplicitQuantitativeCheckResult<double>();
|
|
|
|
EXPECT_NEAR(0.0625, quantitativeResult4[0], storm::settings::nativeEquationSolverSettings().getPrecision());
|
|
|
|
labelFormula = std::make_shared<storm::logic::AtomicLabelFormula>("elected");
|
|
auto reachabilityRewardFormula = std::make_shared<storm::logic::ReachabilityRewardFormula>(labelFormula);
|
|
auto minRewardOperatorFormula = std::make_shared<storm::logic::RewardOperatorFormula>(storm::logic::OptimalityType::Minimize, reachabilityRewardFormula);
|
|
|
|
result = checker.check(*minRewardOperatorFormula);
|
|
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeResult5 = result->asExplicitQuantitativeCheckResult<double>();
|
|
|
|
EXPECT_NEAR(4.285689611, quantitativeResult5[0], storm::settings::nativeEquationSolverSettings().getPrecision());
|
|
|
|
auto maxRewardOperatorFormula = std::make_shared<storm::logic::RewardOperatorFormula>(storm::logic::OptimalityType::Maximize, reachabilityRewardFormula);
|
|
|
|
result = checker.check(*maxRewardOperatorFormula);
|
|
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeResult6 = result->asExplicitQuantitativeCheckResult<double>();
|
|
|
|
EXPECT_NEAR(4.285689611, quantitativeResult6[0], storm::settings::nativeEquationSolverSettings().getPrecision());
|
|
}
|