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prepared Dijkstra-based determination of pivot blocks

tempestpy_adaptions
dehnert 8 years ago
parent
26320049a6
commit
a2bf1643ad
2 changed files with 84 additions and 37 deletions
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  1. 87
      src/storm/abstraction/MenuGameRefiner.cpp
  2. 22
      src/storm/abstraction/MenuGameRefiner.h

87
src/storm/abstraction/MenuGameRefiner.cpp
View File

@ -11,6 +11,18 @@
namespace storm {
namespace abstraction {
RefinementPredicates::RefinementPredicates(Source const& source, std::vector<storm::expressions::Expression> const& predicates) : source(source), predicates(predicates) {
// Intentionally left empty.
}
RefinementPredicates::Source RefinementPredicates::getSource() const {
return source;
}
std::vector<storm::expressions::Expression> const& RefinementPredicates::getPredicates() const {
return predicates;
}
template<storm::dd::DdType Type, typename ValueType>
MenuGameRefiner<Type, ValueType>::MenuGameRefiner(MenuGameAbstractor<Type, ValueType>& abstractor, std::unique_ptr<storm::solver::SmtSolver>&& smtSolver) : abstractor(abstractor), splitPredicates(storm::settings::getModule<storm::settings::modules::AbstractionSettings>().isSplitPredicatesSet()), splitGuards(storm::settings::getModule<storm::settings::modules::AbstractionSettings>().isSplitGuardsSet()), splitter(), equivalenceChecker(std::move(smtSolver)) {
@ -31,7 +43,7 @@ namespace storm {
}
template<storm::dd::DdType Type, typename ValueType>
storm::dd::Bdd<Type> pickPivotStateWithMinimalDistance(storm::dd::Bdd<Type> const& initialStates, storm::dd::Bdd<Type> const& transitionsMin, storm::dd::Bdd<Type> const& transitionsMax, std::set<storm::expressions::Variable> const& rowVariables, std::set<storm::expressions::Variable> const& columnVariables, storm::dd::Bdd<Type> const& pivotStates, boost::optional<QuantitativeResultMinMax<Type, ValueType>> const& quantitativeResult = boost::none) {
std::pair<storm::dd::Bdd<Type>, storm::OptimizationDirection> pickPivotState(storm::dd::Bdd<Type> const& initialStates, storm::dd::Bdd<Type> const& transitionsMin, storm::dd::Bdd<Type> const& transitionsMax, std::set<storm::expressions::Variable> const& rowVariables, std::set<storm::expressions::Variable> const& columnVariables, storm::dd::Bdd<Type> const& pivotStates, boost::optional<QuantitativeResultMinMax<Type, ValueType>> const& quantitativeResult = boost::none) {
// Set up used variables.
storm::dd::Bdd<Type> frontierMin = initialStates;
@ -43,7 +55,7 @@ namespace storm {
bool foundPivotState = !frontierPivotStates.isZero();
if (foundPivotState) {
STORM_LOG_TRACE("Picked pivot state from " << frontierPivotStates.getNonZeroCount() << " candidates on level " << level << ", " << pivotStates.getNonZeroCount() << " candidates in total.");
return frontierPivotStates.existsAbstractRepresentative(rowVariables);
return std::make_pair(frontierPivotStates.existsAbstractRepresentative(rowVariables), storm::OptimizationDirection::Minimize);
} else {
// Otherwise, we perform a simulatenous BFS in the sense that we make one step in both the min and max
@ -52,17 +64,40 @@ namespace storm {
frontierMin = frontierMin.relationalProduct(transitionsMin, rowVariables, columnVariables);
frontierMax = frontierMax.relationalProduct(transitionsMax, rowVariables, columnVariables);
frontierPivotStates = (frontierMin && pivotStates) || (frontierMax && pivotStates);
storm::dd::Bdd<Type> frontierMinPivotStates = frontierMin && pivotStates;
storm::dd::Bdd<Type> frontierMaxPivotStates = frontierMax && pivotStates;
uint64_t numberOfPivotStateCandidatesOnLevel = frontierMinPivotStates.getNonZeroCount() + frontierMaxPivotStates.getNonZeroCount();
if (!frontierPivotStates.isZero()) {
if (!frontierMinPivotStates.isZero() || !frontierMaxPivotStates.isZero()) {
if (quantitativeResult) {
storm::dd::Add<Type, ValueType> frontierPivotStatesAdd = frontierPivotStates.template toAdd<ValueType>();
storm::dd::Add<Type, ValueType> diff = frontierPivotStatesAdd * quantitativeResult.get().max.values - frontierPivotStatesAdd * quantitativeResult.get().min.values;
STORM_LOG_TRACE("Picked pivot state with difference " << diff.getMax() << " from " << frontierPivotStates.getNonZeroCount() << " candidates on level " << level << ", " << pivotStates.getNonZeroCount() << " candidates in total.");
return diff.maxAbstractRepresentative(rowVariables);
storm::dd::Add<Type, ValueType> frontierMinPivotStatesAdd = frontierMinPivotStates.template toAdd<ValueType>();
storm::dd::Add<Type, ValueType> frontierMaxPivotStatesAdd = frontierMaxPivotStates.template toAdd<ValueType>();
storm::dd::Add<Type, ValueType> diffMin = frontierMinPivotStatesAdd * quantitativeResult.get().max.values - frontierMinPivotStatesAdd * quantitativeResult.get().min.values;
storm::dd::Add<Type, ValueType> diffMax = frontierMaxPivotStatesAdd * quantitativeResult.get().max.values - frontierMaxPivotStatesAdd * quantitativeResult.get().min.values;
ValueType diffValue;
storm::OptimizationDirection direction;
if (diffMin.getMax() >= diffMax.getMax()) {
direction = storm::OptimizationDirection::Minimize;
diffValue = diffMin.getMax();
} else {
STORM_LOG_TRACE("Picked pivot state from " << frontierPivotStates.getNonZeroCount() << " candidates on level " << level << ", " << pivotStates.getNonZeroCount() << " candidates in total.");
return frontierPivotStates.existsAbstractRepresentative(rowVariables);
direction = storm::OptimizationDirection::Maximize;
diffValue = diffMax.getMax();
}
STORM_LOG_TRACE("Picked pivot state with difference " << diffValue << " from " << numberOfPivotStateCandidatesOnLevel << " candidates on level " << level << ", " << pivotStates.getNonZeroCount() << " candidates in total.");
return std::make_pair(direction == storm::OptimizationDirection::Minimize ? diffMin.maxAbstractRepresentative(rowVariables) : diffMax.maxAbstractRepresentative(rowVariables), direction);
} else {
STORM_LOG_TRACE("Picked pivot state from " << numberOfPivotStateCandidatesOnLevel << " candidates on level " << level << ", " << pivotStates.getNonZeroCount() << " candidates in total.");
storm::OptimizationDirection direction;
if (!frontierMinPivotStates.isZero()) {
direction = storm::OptimizationDirection::Minimize;
} else {
direction = storm::OptimizationDirection::Maximize;
}
return std::make_pair(direction == storm::OptimizationDirection::Minimize ? frontierMinPivotStates.existsAbstractRepresentative(rowVariables) : frontierMaxPivotStates.existsAbstractRepresentative(rowVariables), direction);
}
}
++level;
@ -70,11 +105,11 @@ namespace storm {
}
STORM_LOG_ASSERT(false, "This point must not be reached, because then no pivot state could be found.");
return storm::dd::Bdd<Type>();
return std::make_pair(storm::dd::Bdd<Type>(), storm::OptimizationDirection::Minimize);
}
template <storm::dd::DdType Type, typename ValueType>
std::pair<storm::expressions::Expression, bool> MenuGameRefiner<Type, ValueType>::derivePredicateFromDifferingChoices(storm::dd::Bdd<Type> const& pivotState, storm::dd::Bdd<Type> const& player1Choice, storm::dd::Bdd<Type> const& lowerChoice, storm::dd::Bdd<Type> const& upperChoice) const {
RefinementPredicates MenuGameRefiner<Type, ValueType>::derivePredicatesFromDifferingChoices(storm::dd::Bdd<Type> const& pivotState, storm::dd::Bdd<Type> const& player1Choice, storm::dd::Bdd<Type> const& lowerChoice, storm::dd::Bdd<Type> const& upperChoice) const {
// Prepare result.
storm::expressions::Expression newPredicate;
bool fromGuard = false;
@ -132,7 +167,7 @@ namespace storm {
for (auto const& predicate : abstractionInformation.getPredicates()) {
STORM_LOG_TRACE(predicate);
}
return std::make_pair(newPredicate, fromGuard);
return RefinementPredicates(fromGuard ? RefinementPredicates::Source::Guard : RefinementPredicates::Source::WeakestPrecondition, {newPredicate});
}
template<storm::dd::DdType Type>
@ -171,7 +206,7 @@ namespace storm {
}
template<storm::dd::DdType Type, typename ValueType>
std::pair<storm::expressions::Expression, bool> MenuGameRefiner<Type, ValueType>::derivePredicateFromPivotState(storm::abstraction::MenuGame<Type, ValueType> const& game, storm::dd::Bdd<Type> const& pivotState, storm::dd::Bdd<Type> const& minPlayer1Strategy, storm::dd::Bdd<Type> const& minPlayer2Strategy, storm::dd::Bdd<Type> const& maxPlayer1Strategy, storm::dd::Bdd<Type> const& maxPlayer2Strategy) const {
RefinementPredicates MenuGameRefiner<Type, ValueType>::derivePredicatesFromPivotState(storm::abstraction::MenuGame<Type, ValueType> const& game, storm::dd::Bdd<Type> const& pivotState, storm::dd::Bdd<Type> const& minPlayer1Strategy, storm::dd::Bdd<Type> const& minPlayer2Strategy, storm::dd::Bdd<Type> const& maxPlayer1Strategy, storm::dd::Bdd<Type> const& maxPlayer2Strategy) const {
// Compute the lower and the upper choice for the pivot state.
std::set<storm::expressions::Variable> variablesToAbstract = game.getNondeterminismVariables();
variablesToAbstract.insert(game.getRowVariables().begin(), game.getRowVariables().end());
@ -184,10 +219,10 @@ namespace storm {
STORM_LOG_TRACE("Refining based on lower choice.");
auto refinementStart = std::chrono::high_resolution_clock::now();
std::pair<storm::expressions::Expression, bool> newPredicate = derivePredicateFromDifferingChoices(pivotState, (pivotState && minPlayer1Strategy).existsAbstract(game.getRowVariables()), lowerChoice1, lowerChoice2);
RefinementPredicates predicates = derivePredicatesFromDifferingChoices(pivotState, (pivotState && minPlayer1Strategy).existsAbstract(game.getRowVariables()), lowerChoice1, lowerChoice2);
auto refinementEnd = std::chrono::high_resolution_clock::now();
STORM_LOG_TRACE("Refinement completed in " << std::chrono::duration_cast<std::chrono::milliseconds>(refinementEnd - refinementStart).count() << "ms.");
return newPredicate;
return predicates;
} else {
storm::dd::Bdd<Type> upperChoice = pivotState && game.getExtendedTransitionMatrix().toBdd() && maxPlayer1Strategy;
storm::dd::Bdd<Type> upperChoice1 = (upperChoice && minPlayer2Strategy).existsAbstract(variablesToAbstract);
@ -197,10 +232,10 @@ namespace storm {
if (upperChoicesDifferent) {
STORM_LOG_TRACE("Refining based on upper choice.");
auto refinementStart = std::chrono::high_resolution_clock::now();
std::pair<storm::expressions::Expression, bool> newPredicate = derivePredicateFromDifferingChoices(pivotState, (pivotState && maxPlayer1Strategy).existsAbstract(game.getRowVariables()), upperChoice1, upperChoice2);
RefinementPredicates predicates = derivePredicatesFromDifferingChoices(pivotState, (pivotState && maxPlayer1Strategy).existsAbstract(game.getRowVariables()), upperChoice1, upperChoice2);
auto refinementEnd = std::chrono::high_resolution_clock::now();
STORM_LOG_TRACE("Refinement completed in " << std::chrono::duration_cast<std::chrono::milliseconds>(refinementEnd - refinementStart).count() << "ms.");
return newPredicate;
return predicates;
} else {
STORM_LOG_ASSERT(false, "Did not find choices from which to derive predicates.");
}
@ -233,11 +268,11 @@ namespace storm {
STORM_LOG_ASSERT(!pivotStateResult.pivotStates.isZero(), "Unable to proceed without pivot state candidates.");
// Now that we have the pivot state candidates, we need to pick one.
storm::dd::Bdd<Type> pivotState = pickPivotStateWithMinimalDistance<Type, ValueType>(game.getInitialStates(), pivotStateResult.reachableTransitionsMin, pivotStateResult.reachableTransitionsMax, game.getRowVariables(), game.getColumnVariables(), pivotStateResult.pivotStates);
std::pair<storm::dd::Bdd<Type>, storm::OptimizationDirection> pivotState = pickPivotState<Type, ValueType>(game.getInitialStates(), pivotStateResult.reachableTransitionsMin, pivotStateResult.reachableTransitionsMax, game.getRowVariables(), game.getColumnVariables(), pivotStateResult.pivotStates);
// Derive predicate based on the selected pivot state.
std::pair<storm::expressions::Expression, bool> newPredicate = derivePredicateFromPivotState(game, pivotState, minPlayer1Strategy, minPlayer2Strategy, maxPlayer1Strategy, maxPlayer2Strategy);
std::vector<storm::expressions::Expression> preparedPredicates = preprocessPredicates({newPredicate.first}, (newPredicate.second && splitGuards) || (!newPredicate.second && splitPredicates));
RefinementPredicates predicates = derivePredicatesFromPivotState(game, pivotState.first, minPlayer1Strategy, minPlayer2Strategy, maxPlayer1Strategy, maxPlayer2Strategy);
std::vector<storm::expressions::Expression> preparedPredicates = preprocessPredicates(predicates.getPredicates(), (predicates.getSource() == RefinementPredicates::Source::Guard && splitGuards) || (predicates.getSource() == RefinementPredicates::Source::WeakestPrecondition && splitPredicates));
performRefinement(createGlobalRefinement(preparedPredicates));
return true;
}
@ -254,18 +289,14 @@ namespace storm {
// Compute all reached pivot states.
PivotStateResult<Type> pivotStateResult = computePivotStates(game, transitionMatrixBdd, minPlayer1Strategy, minPlayer2Strategy, maxPlayer1Strategy, maxPlayer2Strategy);
// TODO: required?
// Require the pivot state to be a state with a lower bound strictly smaller than the upper bound.
pivotStateResult.pivotStates &= quantitativeResult.min.values.less(quantitativeResult.max.values);
STORM_LOG_ASSERT(!pivotStateResult.pivotStates.isZero(), "Unable to refine without pivot state candidates.");
// Now that we have the pivot state candidates, we need to pick one.
storm::dd::Bdd<Type> pivotState = pickPivotStateWithMinimalDistance<Type, ValueType>(game.getInitialStates(), pivotStateResult.reachableTransitionsMin, pivotStateResult.reachableTransitionsMax, game.getRowVariables(), game.getColumnVariables(), pivotStateResult.pivotStates);
std::pair<storm::dd::Bdd<Type>, storm::OptimizationDirection> pivotState = pickPivotState<Type, ValueType>(game.getInitialStates(), pivotStateResult.reachableTransitionsMin, pivotStateResult.reachableTransitionsMax, game.getRowVariables(), game.getColumnVariables(), pivotStateResult.pivotStates);
// Derive predicate based on the selected pivot state.
std::pair<storm::expressions::Expression, bool> newPredicate = derivePredicateFromPivotState(game, pivotState, minPlayer1Strategy, minPlayer2Strategy, maxPlayer1Strategy, maxPlayer2Strategy);
std::vector<storm::expressions::Expression> preparedPredicates = preprocessPredicates({newPredicate.first}, (newPredicate.second && splitGuards) || (!newPredicate.second && splitPredicates));
RefinementPredicates predicates = derivePredicatesFromPivotState(game, pivotState.first, minPlayer1Strategy, minPlayer2Strategy, maxPlayer1Strategy, maxPlayer2Strategy);
std::vector<storm::expressions::Expression> preparedPredicates = preprocessPredicates(predicates.getPredicates(), (predicates.getSource() == RefinementPredicates::Source::Guard && splitGuards) || (predicates.getSource() == RefinementPredicates::Source::WeakestPrecondition && splitPredicates));
performRefinement(createGlobalRefinement(preparedPredicates));
return true;
}

22
src/storm/abstraction/MenuGameRefiner.h
View File

@ -25,6 +25,22 @@ namespace storm {
template <storm::dd::DdType Type, typename ValueType>
class MenuGame;
class RefinementPredicates {
public:
enum class Source {
WeakestPrecondition, Guard, Interpolation
};
RefinementPredicates(Source const& source, std::vector<storm::expressions::Expression> const& predicates);
Source getSource() const;
std::vector<storm::expressions::Expression> const& getPredicates() const;
private:
Source source;
std::vector<storm::expressions::Expression> predicates;
};
template<storm::dd::DdType Type, typename ValueType>
class MenuGameRefiner {
public:
@ -53,13 +69,13 @@ namespace storm {
bool refine(storm::abstraction::MenuGame<Type, ValueType> const& game, storm::dd::Bdd<Type> const& transitionMatrixBdd, QuantitativeResultMinMax<Type, ValueType> const& quantitativeResult) const;
private:
std::pair<storm::expressions::Expression, bool> derivePredicateFromDifferingChoices(storm::dd::Bdd<Type> const& pivotState, storm::dd::Bdd<Type> const& player1Choice, storm::dd::Bdd<Type> const& lowerChoice, storm::dd::Bdd<Type> const& upperChoice) const;
std::pair<storm::expressions::Expression, bool> derivePredicateFromPivotState(storm::abstraction::MenuGame<Type, ValueType> const& game, storm::dd::Bdd<Type> const& pivotState, storm::dd::Bdd<Type> const& minPlayer1Strategy, storm::dd::Bdd<Type> const& minPlayer2Strategy, storm::dd::Bdd<Type> const& maxPlayer1Strategy, storm::dd::Bdd<Type> const& maxPlayer2Strategy) const;
RefinementPredicates derivePredicatesFromDifferingChoices(storm::dd::Bdd<Type> const& pivotState, storm::dd::Bdd<Type> const& player1Choice, storm::dd::Bdd<Type> const& lowerChoice, storm::dd::Bdd<Type> const& upperChoice) const;
RefinementPredicates derivePredicatesFromPivotState(storm::abstraction::MenuGame<Type, ValueType> const& game, storm::dd::Bdd<Type> const& pivotState, storm::dd::Bdd<Type> const& minPlayer1Strategy, storm::dd::Bdd<Type> const& minPlayer2Strategy, storm::dd::Bdd<Type> const& maxPlayer1Strategy, storm::dd::Bdd<Type> const& maxPlayer2Strategy) const;
/*!
* Preprocesses the predicates.
*/
std::vector<storm::expressions::Expression> preprocessPredicates(std::vector<storm::expressions::Expression> const& predicates, bool allowSplits) const;
std::vector<storm::expressions::Expression> preprocessPredicates(std::vector<storm::expressions::Expression> const& predicates, bool split) const;
/*!
* Creates a set of refinement commands that amounts to splitting all player 1 choices with the given set of predicates.

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