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scheduler support for LTL-MC

Conflicts:
	src/storm/storage/Scheduler.cpp
tempestpy_adaptions
hannah 3 years ago
committed by Stefan Pranger
parent
commit
08c454f124
  1. 2
      src/storm/modelchecker/csl/SparseMarkovAutomatonCslModelChecker.cpp
  2. 115
      src/storm/modelchecker/helper/ltl/SparseLTLHelper.cpp
  3. 21
      src/storm/modelchecker/helper/ltl/SparseLTLHelper.h
  4. 2
      src/storm/modelchecker/prctl/SparseDtmcPrctlModelChecker.cpp
  5. 11
      src/storm/modelchecker/prctl/SparseMdpPrctlModelChecker.cpp
  6. 4
      src/storm/modelchecker/prctl/helper/SparseDtmcPrctlHelper.h
  7. 4
      src/storm/storage/Scheduler.cpp
  8. 2
      src/storm/storage/memorystructure/SparseModelMemoryProduct.cpp
  9. 2
      src/storm/transformer/DAProductBuilder.h
  10. 1
      src/storm/transformer/ProductBuilder.h
  11. 53
      src/test/storm/modelchecker/prctl/mdp/SchedulerGenerationMdpPrctlModelCheckerTest.cpp

2
src/storm/modelchecker/csl/SparseMarkovAutomatonCslModelChecker.cpp

@ -144,7 +144,7 @@ namespace storm {
modelDot.close();
}
storm::modelchecker::helper::SparseLTLHelper<ValueType, true> helper(embeddedMdp.getTransitionMatrix(), this->getModel().getNumberOfStates());
storm::modelchecker::helper::SparseLTLHelper<ValueType, true> helper(embeddedMdp.getTransitionMatrix(), embeddedMdp.getNumberOfStates());
storm::modelchecker::helper::setInformationFromCheckTaskNondeterministic(helper, checkTask, embeddedMdp);
// Compute Satisfaction sets for APs

115
src/storm/modelchecker/helper/ltl/SparseLTLHelper.cpp

@ -1,8 +1,5 @@
#include <modelchecker/results/ExplicitQualitativeCheckResult.h>
#include <logic/ExtractMaximalStateFormulasVisitor.h>
#include "SparseLTLHelper.h"
#include "storm/transformer/DAProductBuilder.h"
#include "storm/automata/LTL2DeterministicAutomaton.h"
#include "storm/modelchecker/prctl/helper/SparseDtmcPrctlHelper.h"
@ -10,6 +7,8 @@
#include "storm/storage/StronglyConnectedComponentDecomposition.h"
#include "storm/storage/MaximalEndComponentDecomposition.h"
#include "storm/storage/memorystructure/MemoryStructure.h"
#include "storm/storage/memorystructure/MemoryStructureBuilder.h"
#include "storm/settings/SettingsManager.h"
#include "storm/settings/modules/DebugSettings.h"
@ -26,6 +25,55 @@ namespace storm {
// Intentionally left empty.
}
template <typename ValueType, bool Nondeterministic>
storm::storage::Scheduler<ValueType> SparseLTLHelper<ValueType, Nondeterministic>::SparseLTLHelper::extractScheduler(storm::models::sparse::Model<ValueType> const& model) {
STORM_LOG_ASSERT(this->isProduceSchedulerSet(), "Trying to get the produced optimal choices although no scheduler was requested.");
STORM_LOG_ASSERT(this->_productChoices.is_initialized(), "Trying to extract the produced scheduler but none is available. Was there a computation call before?");
STORM_LOG_ASSERT(this->_memoryTransitions.is_initialized(), "Trying to extract the DA transition structure but none is available. Was there a computation call before?");
STORM_LOG_ASSERT(this->_memoryInitialStates.is_initialized(), "Trying to extract the initial states of the DA but there are none available. Was there a computation call before?");
// Create a memory structure for the MDP scheduler with memory.
typename storm::storage::MemoryStructureBuilder<ValueType>::MemoryStructureBuilder memoryBuilder(this->_memoryTransitions.get().size(), model);
// Build the transitions between the memory states: startState--- modelStates (transitionVector) --->goalState
for (storm::storage::sparse::state_type startState = 0; startState < this->_memoryTransitions.get().size(); ++startState) {
for (storm::storage::sparse::state_type goalState = 0; goalState < this->_memoryTransitions.get().size(); ++goalState) {
// Bitvector that represents modelStates the model states that trigger this transition.
memoryBuilder.setTransition(startState, goalState, this->_memoryTransitions.get()[startState][goalState]);
}
}
/*
memoryStateLabeling: Label the memory states to specify, e.g., accepting states // TODO where are these labels used?
for (storm::storage::sparse::state_type q : set) {
memoryBuilder.setLabel(q,//todo);
}
*/
// initialMemoryStates: Assign an initial memory state to each initial state of the model.
for (uint_fast64_t s0 : model.getInitialStates()) {
// Label the state as initial TODO unnecessary?
//memoryBuilder.setLabel(q, "Initial for model state " s0)
memoryBuilder.setInitialMemoryState(s0, this->_memoryInitialStates.get()[s0]);
}
// Finally, we can build the memoryStructure.
storm::storage::MemoryStructure memoryStructure = memoryBuilder.build();
// Create a scheduler (with memory of size DA) for the model from the scheduler of the MDP-DA-product model.
storm::storage::Scheduler<ValueType> scheduler(this->_transitionMatrix.getRowGroupCount(), memoryStructure);
// Use choices in the product model to create a choice based on model state and memory state
for (const auto &choice : this->_productChoices.get()) {
uint_fast64_t modelState = choice.first.first;
uint_fast64_t memoryState = choice.first.second;
scheduler.setChoice(choice.second, modelState, memoryState);
}
return scheduler;
}
template<typename ValueType, bool Nondeterministic>
std::map<std::string, storm::storage::BitVector> SparseLTLHelper<ValueType, Nondeterministic>::computeApSets(std::map<std::string, std::shared_ptr<storm::logic::Formula const>> const& extracted, std::function<std::unique_ptr<CheckResult>(std::shared_ptr<storm::logic::Formula const> const& formula)> formulaChecker){
std::map<std::string, storm::storage::BitVector> apSets;
@ -141,7 +189,10 @@ namespace storm {
if (accepting) {
accMECs++;
STORM_LOG_DEBUG("MEC is accepting");
for (auto const& stateChoicePair : mec) {
// TODO extend scheduler by mec choices (which?)
// need adversary which forces (to remain in mec and) to visit all states of the mec inf. often with prob. 1
acceptingStates.set(stateChoicePair.first);
}
}
@ -180,12 +231,13 @@ namespace storm {
std::vector<ValueType> SparseLTLHelper<ValueType, Nondeterministic>::computeDAProductProbabilities(Environment const& env, storm::automata::DeterministicAutomaton const& da, std::map<std::string, storm::storage::BitVector>& apSatSets) {
const storm::automata::APSet& apSet = da.getAPSet();
std::vector<storm::storage::BitVector> apLabels;
std::vector<storm::storage::BitVector> statesForAP;
for (const std::string& ap : apSet.getAPs()) {
auto it = apSatSets.find(ap);
STORM_LOG_THROW(it != apSatSets.end(), storm::exceptions::InvalidOperationException, "Deterministic automaton has AP " << ap << ", does not appear in formula");
apLabels.push_back(std::move(it->second));
statesForAP.push_back(std::move(it->second));
}
storm::storage::BitVector statesOfInterest;
@ -199,9 +251,10 @@ namespace storm {
STORM_LOG_INFO("Building "+ (Nondeterministic ? std::string("MDP-DA") : std::string("DTMC-DA")) +"product with deterministic automaton, starting from " << statesOfInterest.getNumberOfSetBits() << " model states...");
storm::transformer::DAProductBuilder productBuilder(da, apLabels);
transformer::DAProductBuilder productBuilder(da, statesForAP);
typename transformer::DAProduct<productModelType>::ptr product = productBuilder.build<productModelType>(this->_transitionMatrix, statesOfInterest);
auto product = productBuilder.build<productModelType>(this->_transitionMatrix, statesOfInterest);
STORM_LOG_INFO("Product "+ (Nondeterministic ? std::string("MDP-DA") : std::string("DTMC-DA")) +" has " << product->getProductModel().getNumberOfStates() << " states and "
<< product->getProductModel().getNumberOfTransitions() << " transitions.");
@ -254,15 +307,56 @@ namespace storm {
if (Nondeterministic) {
prodNumericResult = std::move(storm::modelchecker::helper::SparseMdpPrctlHelper<ValueType>::computeUntilProbabilities(env,
MDPSparseModelCheckingHelperReturnType<ValueType> prodCheckResult = storm::modelchecker::helper::SparseMdpPrctlHelper<ValueType>::computeUntilProbabilities(env,
std::move(solveGoalProduct),
product->getProductModel().getTransitionMatrix(),
product->getProductModel().getBackwardTransitions(),
bvTrue,
acceptingStates,
this->isQualitativeSet(),
false // no schedulers (at the moment)
).values);
this->isProduceSchedulerSet() // Whether to create memoryless scheduler for the Model-DA Product.
);
prodNumericResult = std::move(prodCheckResult.values);
if (this->isProduceSchedulerSet()) {
// Extract the choices of the scheduler for the MDP-DA product: <s,q> -> choice
this->_productChoices.emplace();
for (storm::storage::sparse::state_type pState = 0;
pState < product->getProductModel().getNumberOfStates(); ++pState) {
this->_productChoices.get().insert({std::make_pair(product->getModelState(pState), product->getAutomatonState(pState)), prodCheckResult.scheduler->getChoice(pState)});
}
// Prepare the memory structure. For that, we need: transitions, initialMemoryStates (and todo: memoryStateLabeling)
// The next move function of the memory, will be build based on the transitions of the DA.
this->_memoryTransitions.emplace(da.getNumberOfStates(), std::vector<storm::storage::BitVector>(da.getNumberOfStates()));
for (storm::storage::sparse::state_type startState = 0; startState < da.getNumberOfStates(); ++startState) {
for (storm::storage::sparse::state_type goalState = 0;
goalState < da.getNumberOfStates(); ++goalState) {
// Bitvector that represents modelStates the model states that trigger this transition.
storm::storage::BitVector modelStates(this->_transitionMatrix.getRowGroupCount(), false);
for (storm::storage::sparse::state_type modelState = 0;
modelState < this->_transitionMatrix.getRowGroupCount(); ++modelState) {
if (goalState == productBuilder.getSuccessor(modelState, startState, modelState)) {
modelStates.set(modelState);
}
}
// Insert a transition: startState--{modelStates}-->goalState
this->_memoryTransitions.get()[startState][goalState] = std::move(modelStates);
}
}
this->_memoryInitialStates.emplace();
this->_memoryInitialStates->resize(this->_transitionMatrix.getRowGroupCount());
// Save for each automaton state for which model state it is initial.
for (storm::storage::sparse::state_type modelState = 0; modelState< this->_transitionMatrix.getRowGroupCount(); ++modelState) {
this->_memoryInitialStates.get().at(modelState) = productBuilder.getInitialState(modelState);
}
// TODO labels (e.g. the accepting set?) for the automaton states
}
} else {
prodNumericResult = storm::modelchecker::helper::SparseDtmcPrctlHelper<ValueType>::computeUntilProbabilities(env,
@ -275,6 +369,7 @@ namespace storm {
}
std::vector<ValueType> numericResult = product->projectToOriginalModel(this->_numberOfStates, prodNumericResult);
return numericResult;
}

21
src/storm/modelchecker/helper/ltl/SparseLTLHelper.h

@ -1,10 +1,12 @@
#include "storm/modelchecker/helper/SingleValueModelCheckerHelper.h"
#include "storm/modelchecker/results/ExplicitQualitativeCheckResult.h"
#include "storm/automata/DeterministicAutomaton.h"
#include "storm/storage/SparseMatrix.h"
#include "storm/solver/SolveGoal.h"
#include "storm/models/sparse/Dtmc.h"
#include "storm/models/sparse/Mdp.h"
#include "storm/logic/ExtractMaximalStateFormulasVisitor.h"
#include "storm/transformer/DAProductBuilder.h"
namespace storm {
@ -34,6 +36,14 @@ namespace storm {
*/
SparseLTLHelper(storm::storage::SparseMatrix<ValueType> const& transitionMatrix, std::size_t numberOfSates);
/*!
* @pre before calling this, a computation call should have been performed during which scheduler production was enabled.
* @param TODO
* @return a new scheduler containing optimal choices for each state that yield the long run average values of the most recent call.
*/
storm::storage::Scheduler<ValueType> extractScheduler(storm::models::sparse::Model<ValueType> const& model);
/*!
* todo computes Sat sets of AP
* @param
@ -73,18 +83,23 @@ namespace storm {
* @param the transition matrix of the model
* @param the reversed transition relation
*/
static storm::storage::BitVector computeAcceptingECs(automata::AcceptanceCondition const& acceptance, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, storm::storage::SparseMatrix<ValueType> const& backwardTransitions);
storm::storage::BitVector computeAcceptingECs(automata::AcceptanceCondition const& acceptance, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, storm::storage::SparseMatrix<ValueType> const& backwardTransitions);
/**
* Compute a set S of states that are contained in BSCCs that satisfy the given acceptance conditon.
* @tparam the acceptance condition
* @tparam the transition matrix of the model
*/
static storm::storage::BitVector computeAcceptingBCCs(automata::AcceptanceCondition const& acceptance, storm::storage::SparseMatrix<ValueType> const& transitionMatrix);
storm::storage::BitVector computeAcceptingBCCs(automata::AcceptanceCondition const& acceptance, storm::storage::SparseMatrix<ValueType> const& transitionMatrix);
storm::storage::SparseMatrix<ValueType> const& _transitionMatrix;
std::size_t _numberOfStates;
std::size_t _numberOfStates; //TODO just use _transitionMatrix.getRowGroupCount instead?
// scheduler
boost::optional<std::map<std::pair<uint_fast64_t, uint_fast64_t>, storm::storage::SchedulerChoice<ValueType>>> _productChoices; // <s, q> --> choice
boost::optional<std::vector<std::vector<storm::storage::BitVector>>> _memoryTransitions; // BitVector contains the model states that lead from startState to goalSate of teh DA
boost::optional<std::vector<uint_fast64_t>> _memoryInitialStates; // Saves for each modelState which automaton state is reached from the initial state //TODO improve
};
}

2
src/storm/modelchecker/prctl/SparseDtmcPrctlModelChecker.cpp

@ -164,7 +164,7 @@ namespace storm {
modelDot.close();
}
storm::modelchecker::helper::SparseLTLHelper<ValueType, false> helper(dtmc.getTransitionMatrix(), this->getModel().getNumberOfStates());
storm::modelchecker::helper::SparseLTLHelper<ValueType, false> helper(dtmc.getTransitionMatrix(), dtmc.getNumberOfStates());
storm::modelchecker::helper::setInformationFromCheckTaskDeterministic(helper, checkTask, dtmc);
// Compute Satisfaction sets for APs

11
src/storm/modelchecker/prctl/SparseMdpPrctlModelChecker.cpp

@ -14,9 +14,7 @@
#include "storm/logic/FragmentSpecification.h"
#include "storm/transformer/DAProductBuilder.h"
#include "storm/logic/ExtractMaximalStateFormulasVisitor.h"
#include "storm/automata/LTL2DeterministicAutomaton.h"
#include "storm/models/sparse/StandardRewardModel.h"
@ -199,6 +197,7 @@ namespace storm {
modelDot.close();
}
storm::modelchecker::helper::SparseLTLHelper<ValueType, true> helper(mdp.getTransitionMatrix(), mdp.getNumberOfStates());
storm::modelchecker::helper::setInformationFromCheckTaskNondeterministic(helper, checkTask, mdp);
@ -208,7 +207,13 @@ namespace storm {
std::vector<ValueType> numericResult = helper.computeLTLProbabilities(env, *ltlFormula, apSets);
return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(std::move(numericResult)));
//TODO for MA too
std::unique_ptr<CheckResult> result(new ExplicitQuantitativeCheckResult<ValueType>(std::move(numericResult)));
if (checkTask.isProduceSchedulersSet()) {
result->asExplicitQuantitativeCheckResult<ValueType>().setScheduler(std::make_unique<storm::storage::Scheduler<ValueType>>(helper.extractScheduler(mdp)));
}
return result;
}
template<typename SparseMdpModelType>

4
src/storm/modelchecker/prctl/helper/SparseDtmcPrctlHelper.h

@ -19,10 +19,6 @@ namespace storm {
// fwd
class Environment;
namespace automata {
class DeterministicAutomaton;
}
namespace models {
namespace sparse {
template <typename ValueType, typename RewardModelType> class Dtmc;

4
src/storm/storage/Scheduler.cpp

@ -224,6 +224,10 @@ namespace storm {
out << "Skipped " << numOfSkippedStatesWithUniqueChoice << " deterministic states with unique choice." << std::endl;
}
out << "___________________________________________________________________" << std::endl;
// TODO only for tests:
out << memoryStructure->toString();
out << std::endl;
}
template <>

2
src/storm/storage/memorystructure/SparseModelMemoryProduct.cpp

@ -288,7 +288,7 @@ namespace storm {
uint64_t transitionId = entryIt - model.getTransitionMatrix().begin();
uint64_t successorMemoryState = memorySuccessors[transitionId * memoryStateCount + memoryState];
builder.addNextValue(currentRow, getResultState(entryIt->getColumn(), successorMemoryState), entryIt->getValue());
}
} //TODO successor MemoryState is a problem here 8382838738483264 oder so
} else {
std::map<uint64_t, ValueType> transitions;
for (auto const& choiceIndex : choice.getChoiceAsDistribution()) {

2
src/storm/transformer/DAProductBuilder.h

@ -35,7 +35,7 @@ namespace storm {
return da.getSuccessor(da.getInitialState(), getLabelForState(modelState));
}
storm::storage::sparse::state_type getSuccessor(storm::storage::sparse::state_type modelFrom,
storm::storage::sparse::state_type getSuccessor(storm::storage::sparse::state_type modelFrom, //TODO delete modelFrom?
storm::storage::sparse::state_type automatonFrom,
storm::storage::sparse::state_type modelTo) const {
return da.getSuccessor(automatonFrom, getLabelForState(modelTo));

1
src/storm/transformer/ProductBuilder.h

@ -33,7 +33,6 @@ namespace storm {
// use of the SparseMatrixBuilder that can only handle linear addNextValue
// calls
std::deque<state_type> todo;
for (state_type s_0 : statesOfInterest) {
state_type q_0 = prodOp.getInitialState(s_0);

53
src/test/storm/modelchecker/prctl/mdp/SchedulerGenerationMdpPrctlModelCheckerTest.cpp

@ -173,6 +173,7 @@ namespace {
EXPECT_TRUE(scheduler.isDeterministicScheduler());
EXPECT_TRUE(scheduler.isMemorylessScheduler());
EXPECT_TRUE(!scheduler.isPartialScheduler());
auto inducedModel = mdp->applyScheduler(scheduler);
ASSERT_EQ(inducedModel->getType(), storm::models::ModelType::Mdp);
auto const& inducedMdp = inducedModel->template as<storm::models::sparse::Mdp<ValueType>>();
@ -202,4 +203,56 @@ namespace {
}
}
TYPED_TEST(SchedulerGenerationMdpPrctlModelCheckerTest, ltl) {
typedef typename TestFixture::ValueType ValueType;
std::string formulasString = "Pmax=? [X X \"target\"]; Pmin=? [G F \"target\"];";
auto modelFormulas = this->buildModelFormulas(STORM_TEST_RESOURCES_DIR "/mdp/scheduler_generation.nm", formulasString);
auto mdp = std::move(modelFormulas.first);
auto tasks = this->getTasks(modelFormulas.second);
EXPECT_EQ(4ull, mdp->getNumberOfStates());
EXPECT_EQ(11ull, mdp->getNumberOfTransitions());
ASSERT_EQ(mdp->getType(), storm::models::ModelType::Mdp);
EXPECT_EQ(7ull, mdp->getNumberOfChoices());
storm::modelchecker::SparseMdpPrctlModelChecker<storm::models::sparse::Mdp<ValueType>> checker(*mdp);
{
auto result = checker.check(this->env(), tasks[0]);
ASSERT_TRUE(result->isExplicitQuantitativeCheckResult());
ASSERT_TRUE(result->template asExplicitQuantitativeCheckResult<ValueType>().hasScheduler());
storm::storage::Scheduler<ValueType> const& scheduler = result->template asExplicitQuantitativeCheckResult<ValueType>().getScheduler();
EXPECT_TRUE(scheduler.isDeterministicScheduler());
EXPECT_TRUE(! scheduler.isMemorylessScheduler());
EXPECT_TRUE(scheduler.isPartialScheduler());
auto inducedModel = mdp->applyScheduler(scheduler);
ASSERT_EQ(inducedModel->getType(), storm::models::ModelType::Mdp);
auto const& inducedMdp = inducedModel->template as<storm::models::sparse::Mdp<ValueType>>();
EXPECT_EQ(inducedMdp->getNumberOfChoices(), inducedMdp->getNumberOfStates());
storm::modelchecker::SparseMdpPrctlModelChecker<storm::models::sparse::Mdp<ValueType>> inducedChecker(*inducedMdp);
auto inducedResult = inducedChecker.check(this->env(), tasks[0]);
ASSERT_TRUE(inducedResult->isExplicitQuantitativeCheckResult());
EXPECT_NEAR(this->parseNumber("9/10"), inducedResult->template asExplicitQuantitativeCheckResult<ValueType>()[*mdp->getInitialStates().begin()], storm::settings::getModule<storm::settings::modules::GeneralSettings>().getPrecision());
}
{
auto result = checker.check(this->env(), tasks[1]);
ASSERT_TRUE(result->isExplicitQuantitativeCheckResult());
ASSERT_TRUE(result->template asExplicitQuantitativeCheckResult<ValueType>().hasScheduler());
storm::storage::Scheduler<ValueType> const& scheduler = result->template asExplicitQuantitativeCheckResult<ValueType>().getScheduler();
EXPECT_TRUE(scheduler.isDeterministicScheduler());
EXPECT_TRUE(!scheduler.isMemorylessScheduler());
EXPECT_TRUE(scheduler.isPartialScheduler());
auto inducedModel = mdp->applyScheduler(scheduler);
ASSERT_EQ(inducedModel->getType(), storm::models::ModelType::Mdp);
auto const& inducedMdp = inducedModel->template as<storm::models::sparse::Mdp<ValueType>>();
EXPECT_EQ(inducedMdp->getNumberOfChoices(), inducedMdp->getNumberOfStates());
storm::modelchecker::SparseMdpPrctlModelChecker<storm::models::sparse::Mdp<ValueType>> inducedChecker(*inducedMdp);
auto inducedResult = inducedChecker.check(this->env(), tasks[1]);
ASSERT_TRUE(inducedResult->isExplicitQuantitativeCheckResult());
EXPECT_NEAR(this->parseNumber("1/2"), inducedResult->template asExplicitQuantitativeCheckResult<ValueType>()[*mdp->getInitialStates().begin()], storm::settings::getModule<storm::settings::modules::GeneralSettings>().getPrecision());
}
}
}
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