sp
/
tempest
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity
Browse Source

fixed a bug that prevented correct strategy generation in iterative solver 

Former-commit-id: 1df15b439d
tempestpy_adaptions
dehnert 8 years ago
parent
20f07bf291
commit
a663a37e21
3 changed files with 75 additions and 36 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Unified View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 20
      src/abstraction/prism/AbstractProgram.cpp
  2. 89
      src/modelchecker/abstraction/GameBasedMdpModelChecker.cpp
  3. 2
      src/solver/SymbolicGameSolver.cpp

20
src/abstraction/prism/AbstractProgram.cpp
View File

@ -249,12 +249,14 @@ namespace storm {
// Construct the transition matrix by cutting away the transitions of unreachable states. // Construct the transition matrix by cutting away the transitions of unreachable states.
storm::dd::Add<DdType, ValueType> transitionMatrix = (game.bdd && reachableStates).template toAdd<ValueType>() * commandUpdateProbabilitiesAdd + deadlockTransitions; storm::dd::Add<DdType, ValueType> transitionMatrix = (game.bdd && reachableStates).template toAdd<ValueType>() * commandUpdateProbabilitiesAdd + deadlockTransitions;
// If there are bottom states, we need to mark all other states as non-bottom now.
// Extend the current game information with the 'non-bottom' tag before potentially adding bottom state transitions.
transitionMatrix *= (abstractionInformation.getBottomStateBdd(true, true) && abstractionInformation.getBottomStateBdd(false, true)).template toAdd<ValueType>();
reachableStates &= abstractionInformation.getBottomStateBdd(true, true);
initialStates &= abstractionInformation.getBottomStateBdd(true, true);
// If there are bottom transitions, exnted the transition matrix and reachable states now.
if (hasBottomStates) { if (hasBottomStates) {
transitionMatrix *= (abstractionInformation.getBottomStateBdd(true, true) && abstractionInformation.getBottomStateBdd(false, true)).template toAdd<ValueType>();
transitionMatrix += bottomStateResult.transitions.template toAdd<ValueType>(); transitionMatrix += bottomStateResult.transitions.template toAdd<ValueType>();
reachableStates &= abstractionInformation.getBottomStateBdd(true, true);
initialStates &= abstractionInformation.getBottomStateBdd(true, true);
reachableStates |= bottomStateResult.states; reachableStates |= bottomStateResult.states;
} }
@ -264,15 +266,11 @@ namespace storm {
allNondeterminismVariables.insert(abstractionInformation.getPlayer1Variables().begin(), abstractionInformation.getPlayer1Variables().end()); allNondeterminismVariables.insert(abstractionInformation.getPlayer1Variables().begin(), abstractionInformation.getPlayer1Variables().end());
std::set<storm::expressions::Variable> allSourceVariables(abstractionInformation.getSourceVariables()); std::set<storm::expressions::Variable> allSourceVariables(abstractionInformation.getSourceVariables());
if (hasBottomStates) {
allSourceVariables.insert(abstractionInformation.getBottomStateVariable(true));
}
allSourceVariables.insert(abstractionInformation.getBottomStateVariable(true));
std::set<storm::expressions::Variable> allSuccessorVariables(abstractionInformation.getSuccessorVariables()); std::set<storm::expressions::Variable> allSuccessorVariables(abstractionInformation.getSuccessorVariables());
if (hasBottomStates) {
allSuccessorVariables.insert(abstractionInformation.getBottomStateVariable(false));
}
allSuccessorVariables.insert(abstractionInformation.getBottomStateVariable(false));
return std::make_unique<MenuGame<DdType, ValueType>>(abstractionInformation.getDdManagerAsSharedPointer(), reachableStates, initialStates, abstractionInformation.getDdManager().getBddZero(), transitionMatrix, bottomStateResult.states, allSourceVariables, allSuccessorVariables, hasBottomStates ? abstractionInformation.getExtendedSourceSuccessorVariablePairs() : abstractionInformation.getSourceSuccessorVariablePairs(), std::set<storm::expressions::Variable>(abstractionInformation.getPlayer1Variables().begin(), abstractionInformation.getPlayer1Variables().end()), usedPlayer2Variables, allNondeterminismVariables, auxVariables, abstractionInformation.getPredicateToBddMap());
return std::make_unique<MenuGame<DdType, ValueType>>(abstractionInformation.getDdManagerAsSharedPointer(), reachableStates, initialStates, abstractionInformation.getDdManager().getBddZero(), transitionMatrix, bottomStateResult.states, allSourceVariables, allSuccessorVariables, abstractionInformation.getExtendedSourceSuccessorVariablePairs(), std::set<storm::expressions::Variable>(abstractionInformation.getPlayer1Variables().begin(), abstractionInformation.getPlayer1Variables().end()), usedPlayer2Variables, allNondeterminismVariables, auxVariables, abstractionInformation.getPredicateToBddMap());
} }
template <storm::dd::DdType DdType, typename ValueType> template <storm::dd::DdType DdType, typename ValueType>

89
src/modelchecker/abstraction/GameBasedMdpModelChecker.cpp
View File

@ -234,6 +234,48 @@ namespace storm {
} }
} }
} }
template<storm::dd::DdType Type, typename ValueType>
void refineAfterQuantitativeCheck(storm::abstraction::prism::PrismMenuGameAbstractor<Type, ValueType>& abstractor, storm::abstraction::MenuGame<Type, ValueType> const& game, std::pair<storm::dd::Bdd<Type>, storm::dd::Bdd<Type>> const& minStrategyPair, std::pair<storm::dd::Bdd<Type>, storm::dd::Bdd<Type>> const& maxStrategyPair, storm::dd::Bdd<Type> const& transitionMatrixBdd) {
// Build the fragment of states that is reachable by any combination of the player 1 and player 2 strategies.
storm::dd::Bdd<Type> reachableTransitions = minStrategyPair.second || maxStrategyPair.second;
reachableTransitions = (minStrategyPair.first && reachableTransitions) || (maxStrategyPair.first && reachableTransitions);
reachableTransitions &= transitionMatrixBdd;
reachableTransitions = reachableTransitions.existsAbstract(game.getNondeterminismVariables());
storm::dd::Bdd<Type> pivotStates = storm::utility::dd::computeReachableStates(game.getInitialStates(), reachableTransitions, game.getRowVariables(), game.getColumnVariables());
// Then constrain these states by the requirement that for either the lower or upper player 1 choice the player 2 choices must be different.
pivotStates &= ((minStrategyPair.first || maxStrategyPair.first) && (minStrategyPair.second.exclusiveOr(maxStrategyPair.second))).existsAbstract(game.getNondeterminismVariables());
STORM_LOG_ASSERT(!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 = pickPivotState<Type>(game.getInitialStates(), reachableTransitions, game.getRowVariables(), game.getColumnVariables(), pivotStates);
// 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());
storm::dd::Bdd<Type> lowerChoice = pivotState && game.getExtendedTransitionMatrix().toBdd() && minStrategyPair.first;
storm::dd::Bdd<Type> lowerChoice1 = (lowerChoice && minStrategyPair.second).existsAbstract(variablesToAbstract);
storm::dd::Bdd<Type> lowerChoice2 = (lowerChoice && maxStrategyPair.second).existsAbstract(variablesToAbstract);
bool lowerChoicesDifferent = !lowerChoice1.exclusiveOr(lowerChoice2).isZero();
if (lowerChoicesDifferent) {
STORM_LOG_TRACE("Refining based on lower choice.");
abstractor.refine(pivotState, (pivotState && minStrategyPair.first).existsAbstract(game.getRowVariables()), lowerChoice1, lowerChoice2);
} else {
storm::dd::Bdd<Type> upperChoice = pivotState && game.getExtendedTransitionMatrix().toBdd() && maxStrategyPair.first;
storm::dd::Bdd<Type> upperChoice1 = (upperChoice && minStrategyPair.second).existsAbstract(variablesToAbstract);
storm::dd::Bdd<Type> upperChoice2 = (upperChoice && maxStrategyPair.second).existsAbstract(variablesToAbstract);
bool upperChoicesDifferent = !upperChoice1.exclusiveOr(upperChoice2).isZero();
if (upperChoicesDifferent) {
STORM_LOG_TRACE("Refining based on upper choice.");
abstractor.refine(pivotState, (pivotState && maxStrategyPair.first).existsAbstract(game.getRowVariables()), upperChoice1, upperChoice2);
} else {
STORM_LOG_ASSERT(false, "Did not find choices from which to derive predicates.");
}
}
}
template<storm::dd::DdType Type, typename ValueType> template<storm::dd::DdType Type, typename ValueType>
struct MaybeStateResult { struct MaybeStateResult {
@ -275,17 +317,8 @@ namespace storm {
storm::utility::solver::SymbolicGameSolverFactory<Type, ValueType> solverFactory; storm::utility::solver::SymbolicGameSolverFactory<Type, ValueType> solverFactory;
std::unique_ptr<storm::solver::SymbolicGameSolver<Type, ValueType>> solver = solverFactory.create(submatrix, maybeStates, game.getIllegalPlayer1Mask(), game.getIllegalPlayer2Mask(), game.getRowVariables(), game.getColumnVariables(), game.getRowColumnMetaVariablePairs(), game.getPlayer1Variables(), game.getPlayer2Variables()); std::unique_ptr<storm::solver::SymbolicGameSolver<Type, ValueType>> solver = solverFactory.create(submatrix, maybeStates, game.getIllegalPlayer1Mask(), game.getIllegalPlayer2Mask(), game.getRowVariables(), game.getColumnVariables(), game.getRowColumnMetaVariablePairs(), game.getPlayer1Variables(), game.getPlayer2Variables());
solver->setGeneratePlayersStrategies(true); solver->setGeneratePlayersStrategies(true);
auto values = solver->solveGame(player1Direction, player2Direction, startVector, subvector);
storm::dd::Bdd<Type> player1Strategy = solver->getPlayer1Strategy();
storm::dd::Bdd<Type> player2Strategy = solver->getPlayer2Strategy();
// If we were given a starting point, we fix the strategies now. That is, we only deviate from the
if (startInfo) {
player1Strategy = values.greater(startInfo.get().values).ite(player1Strategy, startInfo.get().player1Strategy);
player1Strategy = values.greater(startInfo.get().values).ite(player1Strategy, startInfo.get().player1Strategy);
}
return MaybeStateResult<Type, ValueType>(values, player1Strategy, player2Strategy);
auto values = solver->solveGame(player1Direction, player2Direction, startVector, subvector, startInfo ? boost::make_optional(startInfo.get().player1Strategy) : boost::none, startInfo ? boost::make_optional(startInfo.get().player2Strategy) : boost::none);
return MaybeStateResult<Type, ValueType>(values, solver->getPlayer1Strategy(), solver->getPlayer2Strategy());
} }
template<storm::dd::DdType Type, typename ValueType> template<storm::dd::DdType Type, typename ValueType>
@ -380,13 +413,13 @@ namespace storm {
storm::dd::Add<Type, ValueType> initialStatesAdd = game.getInitialStates().template toAdd<ValueType>(); storm::dd::Add<Type, ValueType> initialStatesAdd = game.getInitialStates().template toAdd<ValueType>();
ValueType minValue = (prob01.min.second.states && game.getInitialStates()) == game.getInitialStates() ? storm::utility::one<ValueType>() : storm::utility::zero<ValueType>(); ValueType minValue = (prob01.min.second.states && game.getInitialStates()) == game.getInitialStates() ? storm::utility::one<ValueType>() : storm::utility::zero<ValueType>();
MaybeStateResult<Type, ValueType> minMaybeStateResult;
MaybeStateResult<Type, ValueType> minMaybeStateResult(game.getManager().template getAddZero<ValueType>(), game.getManager().getBddZero(), game.getManager().getBddZero());
if (!maybeMin.isZero()) { if (!maybeMin.isZero()) {
minMaybeStateResult = solveMaybeStates(player1Direction, storm::OptimizationDirection::Minimize, game, maybeMin, prob01.min.second.states); minMaybeStateResult = solveMaybeStates(player1Direction, storm::OptimizationDirection::Minimize, game, maybeMin, prob01.min.second.states);
minResult += minMaybeStateResult.values; minResult += minMaybeStateResult.values;
storm::dd::Add<Type, ValueType> initialStateMin = initialStatesAdd * minResult; storm::dd::Add<Type, ValueType> initialStateMin = initialStatesAdd * minResult;
// Here we can only require a non-zero count of *at most* one, because the result may actually be 0. // Here we can only require a non-zero count of *at most* one, because the result may actually be 0.
STORM_LOG_ASSERT(initialStateMin.getNonZeroCount() <= 1, "Wrong number of results for initial states.");
STORM_LOG_ASSERT(initialStateMin.getNonZeroCount() <= 1, "Wrong number of results for initial states. Expected <= 1, but got " << initialStateMin.getNonZeroCount() << ".");
minValue = initialStateMin.getMax(); minValue = initialStateMin.getMax();
} }
STORM_LOG_TRACE("Obtained quantitative lower bound " << minValue << "."); STORM_LOG_TRACE("Obtained quantitative lower bound " << minValue << ".");
@ -398,15 +431,14 @@ namespace storm {
} }
ValueType maxValue = (prob01.max.second.states && game.getInitialStates()) == game.getInitialStates() ? storm::utility::one<ValueType>() : storm::utility::zero<ValueType>(); ValueType maxValue = (prob01.max.second.states && game.getInitialStates()) == game.getInitialStates() ? storm::utility::one<ValueType>() : storm::utility::zero<ValueType>();
MaybeStateResult<Type, ValueType> maxMaybeStateResult;
MaybeStateResult<Type, ValueType> maxMaybeStateResult(game.getManager().template getAddZero<ValueType>(), game.getManager().getBddZero(), game.getManager().getBddZero());
if (!maybeMax.isZero()) { if (!maybeMax.isZero()) {
// FIXME: fix strategy: only change if improved.
maxMaybeStateResult = solveMaybeStates(player1Direction, storm::OptimizationDirection::Maximize, game, maybeMax, prob01.max.second.states, boost::optional<MaybeStateResult<Type, ValueType>>(minMaybeStateResult));
maxMaybeStateResult = solveMaybeStates(player1Direction, storm::OptimizationDirection::Maximize, game, maybeMax, prob01.max.second.states, boost::make_optional(minMaybeStateResult));
maxResult += maxMaybeStateResult.values; maxResult += maxMaybeStateResult.values;
storm::dd::Add<Type, ValueType> initialStateMax = (initialStatesAdd * maxResult); storm::dd::Add<Type, ValueType> initialStateMax = (initialStatesAdd * maxResult);
// Unlike in the min-case, we can require a non-zero count of 1 here, because if the max was in // Unlike in the min-case, we can require a non-zero count of 1 here, because if the max was in
// fact 0, the result would be 0, which would have been detected earlier by the graph algorithms. // fact 0, the result would be 0, which would have been detected earlier by the graph algorithms.
STORM_LOG_ASSERT(initialStateMax.getNonZeroCount() == 1, "Wrong number of results for initial states.");
STORM_LOG_ASSERT(initialStateMax.getNonZeroCount() == 1, "Wrong number of results for initial states. Expected 1, but got " << initialStateMax.getNonZeroCount() << ".");
maxValue = initialStateMax.getMax(); maxValue = initialStateMax.getMax();
} }
STORM_LOG_TRACE("Obtained quantitative upper bound " << maxValue << "."); STORM_LOG_TRACE("Obtained quantitative upper bound " << maxValue << ".");
@ -427,7 +459,13 @@ namespace storm {
// If we arrived at this point, it means that we have all qualitative and quantitative information // If we arrived at this point, it means that we have all qualitative and quantitative information
// about the game, but we could not yet answer the query. In this case, we need to refine. // about the game, but we could not yet answer the query. In this case, we need to refine.
STORM_LOG_ASSERT(false, "Quantiative refinement not yet there. :)");
// Start by extending the quantitative strategies by the qualitative ones.
minMaybeStateResult.player1Strategy |= prob01.min.first.getPlayer1Strategy() || prob01.min.second.getPlayer1Strategy();
minMaybeStateResult.player2Strategy |= prob01.min.first.getPlayer2Strategy() || prob01.min.second.getPlayer2Strategy();
maxMaybeStateResult.player1Strategy |= prob01.max.first.getPlayer1Strategy() || prob01.max.second.getPlayer1Strategy();
maxMaybeStateResult.player2Strategy |= prob01.max.first.getPlayer2Strategy() || prob01.max.second.getPlayer2Strategy();
refineAfterQuantitativeCheck(abstractor, game, std::make_pair(minMaybeStateResult.player1Strategy, minMaybeStateResult.player2Strategy), std::make_pair(maxMaybeStateResult.player1Strategy, maxMaybeStateResult.player2Strategy), transitionMatrixBdd);
} }
} }
@ -438,15 +476,18 @@ namespace storm {
template<storm::dd::DdType Type, typename ValueType> template<storm::dd::DdType Type, typename ValueType>
std::pair<storm::utility::graph::GameProb01Result<Type>, storm::utility::graph::GameProb01Result<Type>> GameBasedMdpModelChecker<Type, ValueType>::computeProb01States(storm::OptimizationDirection player1Direction, storm::OptimizationDirection player2Direction, storm::abstraction::MenuGame<Type, ValueType> const& game, storm::dd::Bdd<Type> const& transitionMatrixBdd, storm::dd::Bdd<Type> const& constraintStates, storm::dd::Bdd<Type> const& targetStates) { std::pair<storm::utility::graph::GameProb01Result<Type>, storm::utility::graph::GameProb01Result<Type>> GameBasedMdpModelChecker<Type, ValueType>::computeProb01States(storm::OptimizationDirection player1Direction, storm::OptimizationDirection player2Direction, storm::abstraction::MenuGame<Type, ValueType> const& game, storm::dd::Bdd<Type> const& transitionMatrixBdd, storm::dd::Bdd<Type> const& constraintStates, storm::dd::Bdd<Type> const& targetStates) {
// Compute the states with probability 0/1. // Compute the states with probability 0/1.
storm::utility::graph::GameProb01Result<Type> prob0 = storm::utility::graph::performProb0(game, transitionMatrixBdd, constraintStates, targetStates, player1Direction, player2Direction, player2Direction == storm::OptimizationDirection::Minimize, player2Direction == storm::OptimizationDirection::Minimize);
storm::utility::graph::GameProb01Result<Type> prob1 = storm::utility::graph::performProb1(game, transitionMatrixBdd, constraintStates, targetStates, player1Direction, player2Direction, player2Direction == storm::OptimizationDirection::Maximize, player2Direction == storm::OptimizationDirection::Maximize);
// storm::utility::graph::GameProb01Result<Type> prob0 = storm::utility::graph::performProb0(game, transitionMatrixBdd, constraintStates, targetStates, player1Direction, player2Direction, player2Direction == storm::OptimizationDirection::Minimize, player2Direction == storm::OptimizationDirection::Minimize);
// storm::utility::graph::GameProb01Result<Type> prob1 = storm::utility::graph::performProb1(game, transitionMatrixBdd, constraintStates, targetStates, player1Direction, player2Direction, player2Direction == storm::OptimizationDirection::Maximize, player2Direction == storm::OptimizationDirection::Maximize);
storm::utility::graph::GameProb01Result<Type> prob0 = storm::utility::graph::performProb0(game, transitionMatrixBdd, constraintStates, targetStates, player1Direction, player2Direction, true, true);
storm::utility::graph::GameProb01Result<Type> prob1 = storm::utility::graph::performProb1(game, transitionMatrixBdd, constraintStates, targetStates, player1Direction, player2Direction, true, true);
STORM_LOG_ASSERT(player2Direction != storm::OptimizationDirection::Minimize || (prob0.hasPlayer1Strategy() && !prob0.getPlayer1Strategy().isZero()), "Unable to proceed without strategy.");
STORM_LOG_ASSERT(player2Direction != storm::OptimizationDirection::Minimize || (prob0.hasPlayer2Strategy() && !prob0.getPlayer2Strategy().isZero()), "Unable to proceed without strategy.");
STORM_LOG_ASSERT(player2Direction != storm::OptimizationDirection::Maximize || (prob1.hasPlayer1Strategy() && !prob1.getPlayer1Strategy().isZero()), "Unable to proceed without strategy.");
STORM_LOG_ASSERT(player2Direction != storm::OptimizationDirection::Maximize || (prob1.hasPlayer2Strategy() && !prob1.getPlayer2Strategy().isZero()), "Unable to proceed without strategy.");
STORM_LOG_ASSERT(player2Direction != storm::OptimizationDirection::Minimize || (prob0.hasPlayer1Strategy() && (prob0.states.isZero() || !prob0.getPlayer1Strategy().isZero())), "Unable to proceed without strategy.");
STORM_LOG_ASSERT(player2Direction != storm::OptimizationDirection::Minimize || (prob0.hasPlayer2Strategy() && (prob0.states.isZero() || !prob0.getPlayer2Strategy().isZero())), "Unable to proceed without strategy.");
STORM_LOG_ASSERT(player2Direction != storm::OptimizationDirection::Maximize || (prob1.hasPlayer1Strategy() && (prob1.states.isZero() || !prob1.getPlayer1Strategy().isZero())), "Unable to proceed without strategy.");
STORM_LOG_ASSERT(player2Direction != storm::OptimizationDirection::Maximize || (prob1.hasPlayer2Strategy() && (prob1.states.isZero() || !prob1.getPlayer2Strategy().isZero())), "Unable to proceed without strategy.");
STORM_LOG_TRACE("Player 1: " << player1Direction << ", player 2: " << player2Direction << ": " << prob0.states.getNonZeroCount() << " 'no' states, " << prob1.states.getNonZeroCount() << " 'yes' states."); STORM_LOG_TRACE("Player 1: " << player1Direction << ", player 2: " << player2Direction << ": " << prob0.states.getNonZeroCount() << " 'no' states, " << prob1.states.getNonZeroCount() << " 'yes' states.");
return std::make_pair(prob0, prob1); return std::make_pair(prob0, prob1);
} }

2
src/solver/SymbolicGameSolver.cpp
View File

@ -46,7 +46,7 @@ namespace storm {
// If we are required to generate a player 2 strategy based on another one that is not the zero strategy, // If we are required to generate a player 2 strategy based on another one that is not the zero strategy,
// we need to determine the values, because only then we can update the strategy only if necessary. // we need to determine the values, because only then we can update the strategy only if necessary.
previousPlayer2Values = ((this->A * player2Strategy.get().template toAdd<ValueType>()).multiplyMatrix(x.swapVariables(this->rowColumnMetaVariablePairs), this->columnMetaVariables) + b).sumAbstract(this->player2Variables);
previousPlayer2Values = (player2Strategy.get().template toAdd<ValueType>() * (this->A.multiplyMatrix(x.swapVariables(this->rowColumnMetaVariablePairs), this->columnMetaVariables) + b)).sumAbstract(this->player2Variables);
} else { } else {
player2Strategy = A.getDdManager().getBddZero(); player2Strategy = A.getDdManager().getBddZero();
previousPlayer2Values = A.getDdManager().template getAddZero<ValueType>(); previousPlayer2Values = A.getDdManager().template getAddZero<ValueType>();

Write Preview
Loading…
Cancel
Save