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Tweaked LRA computation for MDPs and MAs in sound mode to meet precision requirements.

tempestpy_adaptions
TimQu 6 years ago
parent
5d61329eb3
commit
985319c7dd
2 changed files with 33 additions and 12 deletions
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  1. 23
      src/storm/modelchecker/csl/helper/SparseMarkovAutomatonCslHelper.cpp
  2. 22
      src/storm/modelchecker/prctl/helper/SparseMdpPrctlHelper.cpp

23
src/storm/modelchecker/csl/helper/SparseMarkovAutomatonCslHelper.cpp
View File

@ -12,6 +12,7 @@
#include "storm/settings/modules/MinMaxEquationSolverSettings.h"
#include "storm/environment/Environment.h"
#include "storm/environment/solver/MinMaxSolverEnvironment.h"
#include "storm/utility/macros.h"
#include "storm/utility/vector.h"
@ -655,6 +656,12 @@ namespace storm {
std::vector<uint64_t> stateToMecIndexMap(numberOfStates);
storm::storage::BitVector statesInMecs(numberOfStates);
auto underlyingSolverEnvironment = env;
if (env.solver().isForceSoundness()) {
// For sound computations, the error in the MECS plus the error in the remaining system should be less then the user defined precsion.
underlyingSolverEnvironment.solver().minMax().setPrecision(env.solver().minMax().getPrecision() / storm::utility::convertNumber<storm::RationalNumber>(2));
}
for (uint64_t currentMecIndex = 0; currentMecIndex < mecDecomposition.size(); ++currentMecIndex) {
storm::storage::MaximalEndComponent const& mec = mecDecomposition[currentMecIndex];
@ -667,7 +674,7 @@ namespace storm {
}
// Compute the LRA value for the current MEC.
lraValuesForEndComponents.push_back(computeLraForMaximalEndComponent(env, dir, transitionMatrix, exitRateVector, markovianStates, rewardModel, mec));
lraValuesForEndComponents.push_back(computeLraForMaximalEndComponent(underlyingSolverEnvironment, dir, transitionMatrix, exitRateVector, markovianStates, rewardModel, mec));
}
// For fast transition rewriting, we build some auxiliary data structures.
@ -770,16 +777,16 @@ namespace storm {
// Check for requirements of the solver.
storm::solver::GeneralMinMaxLinearEquationSolverFactory<ValueType> minMaxLinearEquationSolverFactory;
storm::solver::MinMaxLinearEquationSolverRequirements requirements = minMaxLinearEquationSolverFactory.getRequirements(env, true, dir);
storm::solver::MinMaxLinearEquationSolverRequirements requirements = minMaxLinearEquationSolverFactory.getRequirements(underlyingSolverEnvironment, true, dir);
requirements.clearBounds();
STORM_LOG_THROW(!requirements.hasEnabledCriticalRequirement(), storm::exceptions::UncheckedRequirementException, "Solver requirements " + requirements.getEnabledRequirementsAsString() + " not checked.");
std::unique_ptr<storm::solver::MinMaxLinearEquationSolver<ValueType>> solver = minMaxLinearEquationSolverFactory.create(env, sspMatrix);
std::unique_ptr<storm::solver::MinMaxLinearEquationSolver<ValueType>> solver = minMaxLinearEquationSolverFactory.create(underlyingSolverEnvironment, sspMatrix);
solver->setHasUniqueSolution();
solver->setLowerBound(storm::utility::zero<ValueType>());
solver->setUpperBound(*std::max_element(lraValuesForEndComponents.begin(), lraValuesForEndComponents.end()));
solver->setRequirementsChecked();
solver->solveEquations(env, dir, x, b);
solver->solveEquations(underlyingSolverEnvironment, dir, x, b);
// Prepare result vector.
std::vector<ValueType> result(numberOfStates);
@ -830,6 +837,9 @@ namespace storm {
if (storm::NumberTraits<ValueType>::IsExact && minMaxSettings.isLraMethodSetFromDefaultValue() && method != storm::solver::LraMethod::LinearProgramming) {
STORM_LOG_INFO("Selecting 'LP' as the solution technique for long-run properties to guarantee exact results. If you want to override this, please explicitly specify a different LRA method.");
method = storm::solver::LraMethod::LinearProgramming;
} else if (env.solver().isForceSoundness() && minMaxSettings.isLraMethodSetFromDefaultValue() && method != storm::solver::LraMethod::ValueIteration) {
STORM_LOG_INFO("Selecting 'VI' as the solution technique for long-run properties to guarantee sound results. If you want to override this, please explicitly specify a different LRA method.");
method = storm::solver::LraMethod::ValueIteration;
}
if (method == storm::solver::LraMethod::LinearProgramming) {
return computeLraForMaximalEndComponentLP(env, dir, transitionMatrix, exitRateVector, markovianStates, rewardModel, mec);
@ -980,7 +990,8 @@ namespace storm {
// start the iterations
ValueType precision = storm::utility::convertNumber<ValueType>(storm::settings::getModule<storm::settings::modules::GeneralSettings>().getPrecision()) / uniformizationRate;
ValueType precision = storm::utility::convertNumber<ValueType>(env.solver().minMax().getPrecision()) / uniformizationRate;
bool relative = env.solver().minMax().getRelativeTerminationCriterion();
std::vector<ValueType> v(aMarkovian.getRowCount(), storm::utility::zero<ValueType>());
std::vector<ValueType> w = v;
std::vector<ValueType> x(aProbabilistic.getRowGroupCount(), storm::utility::zero<ValueType>());
@ -1019,7 +1030,7 @@ namespace storm {
}
// Check for convergence
if (maxDiff - minDiff < precision) {
if (maxDiff - minDiff <= relative ? (precision * minDiff) : precision) {
break;
}

22
src/storm/modelchecker/prctl/helper/SparseMdpPrctlHelper.cpp
View File

@ -1328,10 +1328,16 @@ namespace storm {
std::vector<uint_fast64_t> stateToMecIndexMap(transitionMatrix.getColumnCount());
std::vector<ValueType> lraValuesForEndComponents(mecDecomposition.size(), zero);
auto underlyingSolverEnvironment = env;
if (env.solver().isForceSoundness()) {
// For sound computations, the error in the MECS plus the error in the remaining system should be less then the user defined precsion.
underlyingSolverEnvironment.solver().minMax().setPrecision(env.solver().minMax().getPrecision() / storm::utility::convertNumber<storm::RationalNumber>(2));
}
for (uint_fast64_t currentMecIndex = 0; currentMecIndex < mecDecomposition.size(); ++currentMecIndex) {
storm::storage::MaximalEndComponent const& mec = mecDecomposition[currentMecIndex];
lraValuesForEndComponents[currentMecIndex] = computeLraForMaximalEndComponent(env, goal.direction(), transitionMatrix, rewardModel, mec);
lraValuesForEndComponents[currentMecIndex] = computeLraForMaximalEndComponent(underlyingSolverEnvironment, goal.direction(), transitionMatrix, rewardModel, mec);
// Gather information for later use.
for (auto const& stateChoicesPair : mec) {
@ -1438,19 +1444,19 @@ namespace storm {
// Check for requirements of the solver.
storm::solver::GeneralMinMaxLinearEquationSolverFactory<ValueType> minMaxLinearEquationSolverFactory;
storm::solver::MinMaxLinearEquationSolverRequirements requirements = minMaxLinearEquationSolverFactory.getRequirements(env, true, goal.direction());
storm::solver::MinMaxLinearEquationSolverRequirements requirements = minMaxLinearEquationSolverFactory.getRequirements(underlyingSolverEnvironment, true, goal.direction());
requirements.clearBounds();
STORM_LOG_THROW(!requirements.hasEnabledCriticalRequirement(), storm::exceptions::UncheckedRequirementException, "Solver requirements " + requirements.getEnabledRequirementsAsString() + " not checked.");
std::vector<ValueType> sspResult(numberOfSspStates);
goal.restrictRelevantValues(statesNotContainedInAnyMec);
std::unique_ptr<storm::solver::MinMaxLinearEquationSolver<ValueType>> solver = storm::solver::configureMinMaxLinearEquationSolver(env, std::move(goal), minMaxLinearEquationSolverFactory, sspMatrix);
std::unique_ptr<storm::solver::MinMaxLinearEquationSolver<ValueType>> solver = storm::solver::configureMinMaxLinearEquationSolver(underlyingSolverEnvironment, std::move(goal), minMaxLinearEquationSolverFactory, sspMatrix);
solver->setLowerBound(storm::utility::zero<ValueType>());
solver->setUpperBound(*std::max_element(lraValuesForEndComponents.begin(), lraValuesForEndComponents.end()));
solver->setHasUniqueSolution();
solver->setRequirementsChecked();
solver->solveEquations(env, sspResult, b);
solver->solveEquations(underlyingSolverEnvironment, sspResult, b);
// Prepare result vector.
std::vector<ValueType> result(numberOfStates, zero);
@ -1491,6 +1497,9 @@ namespace storm {
if (storm::NumberTraits<ValueType>::IsExact && minMaxSettings.isLraMethodSetFromDefaultValue() && method != storm::solver::LraMethod::LinearProgramming) {
STORM_LOG_INFO("Selecting 'LP' as the solution technique for long-run properties to guarantee exact results. If you want to override this, please explicitly specify a different LRA method.");
method = storm::solver::LraMethod::LinearProgramming;
} else if (env.solver().isForceSoundness() && minMaxSettings.isLraMethodSetFromDefaultValue() && method != storm::solver::LraMethod::ValueIteration) {
STORM_LOG_INFO("Selecting 'VI' as the solution technique for long-run properties to guarantee sound results. If you want to override this, please explicitly specify a different LRA method.");
method = storm::solver::LraMethod::ValueIteration;
}
if (method == storm::solver::LraMethod::LinearProgramming) {
return computeLraForMaximalEndComponentLP(env, dir, transitionMatrix, rewardModel, mec);
@ -1563,7 +1572,8 @@ namespace storm {
STORM_LOG_ASSERT(mecTransitions.isProbabilistic(), "The MEC-Matrix is not probabilistic.");
// start the iterations
ValueType precision = storm::utility::convertNumber<ValueType>(storm::settings::getModule<storm::settings::modules::MinMaxEquationSolverSettings>().getPrecision());
ValueType precision = storm::utility::convertNumber<ValueType>(env.solver().minMax().getPrecision());
bool relative = env.solver().minMax().getRelativeTerminationCriterion();
std::vector<ValueType> x(mecTransitions.getRowGroupCount(), storm::utility::zero<ValueType>());
std::vector<ValueType> xPrime = x;
@ -1590,7 +1600,7 @@ namespace storm {
*xPrimeIt = *xIt;
}
if ((maxDiff - minDiff) < precision) {
if ((maxDiff - minDiff) <= relative ? (precision * minDiff) : precision) {
break;
}
}

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