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generalizing the Selfloop elimination ideo to MECs

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TimQu 8 years ago
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  1. 160
      src/storm-pomdp/transformer/GlobalPomdpMecChoiceEliminator.cpp
  2. 31
      src/storm-pomdp/transformer/GlobalPomdpMecChoiceEliminator.h

160
src/storm-pomdp/transformer/GlobalPomdpMecChoiceEliminator.cpp
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#include "storm-pomdp/transformer/GlobalPomdpMecChoiceEliminator.h"
#include <vector>
#include "storm/transformer/ChoiceSelector.h"
#include "storm/modelchecker/propositional/SparsePropositionalModelChecker.h"
#include "storm/modelchecker/results/ExplicitQualitativeCheckResult.h"
#include "storm/utility/graph.h"
#include "storm/utility/macros.h"
#include "storm/exceptions/InvalidPropertyException.h"
namespace storm {
namespace transformer {
template<typename ValueType>
GlobalPomdpMecChoiceEliminator<ValueType>::GlobalPomdpMecChoiceEliminator(storm::models::sparse::Pomdp<ValueType> const& pomdp) : pomdp(pomdp) {
}
template<typename ValueType>
std::shared_ptr<storm::models::sparse::Pomdp<ValueType>> GlobalPomdpMecChoiceEliminator<ValueType>::transform(storm::logic::Formula const& formula) const {
// check whether the property is minimizing or maximizing
STORM_LOG_THROW(formula.isOperatorFormula(), storm::exceptions::InvalidPropertyException, "Expected an operator formula");
STORM_LOG_THROW(formula.asOperatorFormula().hasOptimalityType() || formula.asOperatorFormula().hasBound(), storm::exceptions::InvalidPropertyException, "The formula " << formula << " does not specify whether to minimize or maximize.");
bool minimizes = (formula.asOperatorFormula().hasOptimalityType() && storm::solver::minimize(formula.asOperatorFormula().getOptimalityType())) || (formula.asOperatorFormula().hasBound() && storm::logic::isLowerBound(formula.asOperatorFormula().getBound().comparisonType));
std::shared_ptr<storm::logic::Formula const> subformula = formula.asOperatorFormula().getSubformula().asSharedPointer();
// If necessary, convert the subformula to a more general case
if (subformula->isEventuallyFormula() && subformula->asEventuallyFormula().isProbabilityPathFormula()) {
subformula = std::make_shared<storm::logic::UntilFormula>(storm::logic::Formula::getTrueFormula(), subformula->asEventuallyFormula().getSubformula().asSharedPointer());
}
if (subformula->isUntilFormula()) {
if (!minimizes) {
return transformMax(subformula->asUntilFormula());
}
}
STORM_LOG_THROW(false, storm::exceptions::InvalidPropertyException, "Mec elimination is not supported for the property " << formula);
}
template<typename ValueType>
std::shared_ptr<storm::models::sparse::Pomdp<ValueType>> GlobalPomdpMecChoiceEliminator<ValueType>::transformMax(storm::logic::UntilFormula const& formula) const {
auto backwardTransitions = pomdp.getBackwardTransitions();
auto prob01States = storm::utility::graph::performProb01Max(pomdp.getTransitionMatrix(), pomdp.getTransitionMatrix().getRowGroupIndices(), backwardTransitions, checkPropositionalFormula(formula.getLeftSubformula()), checkPropositionalFormula(formula.getRightSubformula()));
auto mecs = decomposeEndComponents(~(prob01States.first | prob01States.second), prob01States.first);
std::vector<storm::storage::BitVector> mecChoicesPerObservation(pomdp.getNrObservations());
storm::storage::BitVector uniqueOutStates(pomdp.getNumberOfStates(), false);
// Find the MECs that have only one 'out' state
for (auto const& mec : mecs) {
boost::optional<uint64_t> uniqueOutState = boost::none;
for (auto const& stateActionsPair : mec) {
// Check whether this is an 'out' state, i.e., not all actions stay inside the MEC
if (stateActionsPair.second.size() != pomdp.getNumberOfChoices(stateActionsPair.first)) {
if (uniqueOutState) {
// we already found one out state, so this mec is invalid
uniqueOutState = boost::none;
break;
} else {
uniqueOutState = stateActionsPair.first;
}
}
}
if (uniqueOutState) {
uniqueOutStates.set(uniqueOutState.get(), true);
storm::storage::BitVector localChoiceIndices(pomdp.getNumberOfChoices(uniqueOutState.get()), false);
uint64_t offset = pomdp.getTransitionMatrix().getRowGroupIndices()[uniqueOutState.get()];
for (auto const& choice : mec.getChoicesForState(uniqueOutState.get())) {
assert(choice >= offset);
localChoiceIndices.set(choice - offset, true);
}
auto& mecChoices = mecChoicesPerObservation[pomdp.getObservation(uniqueOutState.get())];
if (mecChoices.size() == 0) {
mecChoices = localChoiceIndices;
} else {
STORM_LOG_ASSERT(mecChoices.size() == localChoiceIndices.size(), "Observation action count does not match for two states with the same observation");
mecChoices &= localChoiceIndices;
}
}
}
// Filter the observations that have a state that is neither an out state, nor a prob0A or prob1A state
storm::storage::BitVector stateFilter = ~(uniqueOutStates | prob01States.first | prob01States.second);
for (auto const& state : stateFilter) {
mecChoicesPerObservation[pomdp.getObservation(state)].clear();
}
// It should not be possible to clear all choices for an observation since we only consider states that lead outside of its MEC.
for (auto& clearedChoices : mecChoicesPerObservation) {
STORM_LOG_ASSERT(clearedChoices.size() == 0 || !clearedChoices.full(), "Tried to clear all choices for an observation.");
}
// transform the set of selected choices to global choice indices
storm::storage::BitVector choiceFilter(pomdp.getNumberOfChoices(), true);
stateFilter.complement();
for (auto const& state : stateFilter) {
uint64_t offset = pomdp.getTransitionMatrix().getRowGroupIndices()[state];
for (auto const& choice : mecChoicesPerObservation[pomdp.getObservation(state)]) {
choiceFilter.set(offset + choice, false);
}
}
ChoiceSelector<ValueType> cs(pomdp);
return cs.transform(choiceFilter)->template as<storm::models::sparse::Pomdp<ValueType>>();
}
template<typename ValueType>
storm::storage::MaximalEndComponentDecomposition<ValueType> GlobalPomdpMecChoiceEliminator<ValueType>::decomposeEndComponents(storm::storage::BitVector const& subsystem, storm::storage::BitVector const& redirectingStates) const {
if (redirectingStates.empty()) {
return storm::storage::MaximalEndComponentDecomposition<ValueType>(pomdp.getTransitionMatrix(), pomdp.getBackwardTransitions(), subsystem);
} else {
// Redirect all incoming transitions of a redirictingState back to the origin of the transition.
storm::storage::SparseMatrixBuilder<ValueType> builder(pomdp.getTransitionMatrix().getRowCount(), pomdp.getTransitionMatrix().getColumnCount(), 0, true, true, pomdp.getTransitionMatrix().getRowGroupCount());
uint64_t row = 0;
for (uint64_t rowGroup = 0; rowGroup < pomdp.getTransitionMatrix().getRowGroupCount(); ++rowGroup) {
assert(row == pomdp.getTransitionMatrix().getRowGroupIndices()[rowGroup]);
builder.newRowGroup(row);
for (; row < pomdp.getTransitionMatrix().getRowGroupIndices()[rowGroup + 1]; ++row) {
ValueType redirectedProbabilityMass = pomdp.getTransitionMatrix().getConstrainedRowSum(row, redirectingStates);
bool insertSelfloop = !storm::utility::isZero(redirectedProbabilityMass);
for (auto const& entry : pomdp.getTransitionMatrix().getRow(row)) {
if (!redirectingStates.get(entry.getColumn())) {
if (insertSelfloop && entry.getColumn() >= rowGroup) {
// insert selfloop now
insertSelfloop = false;
if (entry.getColumn() == rowGroup) {
builder.addNextValue(row, rowGroup, entry.getValue() + redirectedProbabilityMass);
continue;
} else {
builder.addNextValue(row, rowGroup, redirectedProbabilityMass);
}
}
builder.addNextValue(row, entry.getColumn(), entry.getValue());
}
}
if (insertSelfloop) {
builder.addNextValue(row, rowGroup, redirectedProbabilityMass);
}
}
}
storm::storage::SparseMatrix<ValueType> transitionMatrix = builder.build();
return storm::storage::MaximalEndComponentDecomposition<ValueType>(transitionMatrix, transitionMatrix.transpose(true), subsystem);
}
}
template<typename ValueType>
storm::storage::BitVector GlobalPomdpMecChoiceEliminator<ValueType>::checkPropositionalFormula(storm::logic::Formula const& propositionalFormula) const {
storm::modelchecker::SparsePropositionalModelChecker<storm::models::sparse::Mdp<ValueType>> mc(pomdp);
STORM_LOG_THROW(mc.canHandle(propositionalFormula), storm::exceptions::InvalidPropertyException, "Propositional model checker can not handle formula " << propositionalFormula);
return mc.check(propositionalFormula)->asExplicitQualitativeCheckResult().getTruthValuesVector();
}
template class GlobalPomdpMecChoiceEliminator<storm::RationalNumber>;
}
}

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src/storm-pomdp/transformer/GlobalPomdpMecChoiceEliminator.h
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#pragma once
#include "storm/models/sparse/Pomdp.h"
#include "storm/logic/Formulas.h"
#include "storm/storage/BitVector.h"
#include "storm/storage/MaximalEndComponentDecomposition.h"
namespace storm {
namespace transformer {
template<typename ValueType>
class GlobalPomdpMecChoiceEliminator {
public:
GlobalPomdpMecChoiceEliminator(storm::models::sparse::Pomdp<ValueType> const& pomdp);
// Note: this only preserves probabilities for memoryless pomdps
std::shared_ptr<storm::models::sparse::Pomdp<ValueType>> transform(storm::logic::Formula const& formula) const;
private:
std::shared_ptr<storm::models::sparse::Pomdp<ValueType>> transformMax(storm::logic::UntilFormula const& formula) const;
storm::storage::MaximalEndComponentDecomposition<ValueType> decomposeEndComponents(storm::storage::BitVector const& subsystem, storm::storage::BitVector const& ignoredStates) const;
storm::storage::BitVector checkPropositionalFormula(storm::logic::Formula const& propositionalFormula) const;
storm::models::sparse::Pomdp<ValueType> const& pomdp;
};
}
}
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