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conditional probabilities in MDPs should now also work in the min-case 

Former-commit-id: 9b3c22470b
tempestpy_adaptions
dehnert 9 years ago
parent
3e38e73efe
commit
b1c103811b
1 changed files with 26 additions and 11 deletions
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  1. 37
      src/modelchecker/prctl/helper/SparseMdpPrctlHelper.cpp

37
src/modelchecker/prctl/helper/SparseMdpPrctlHelper.cpp
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@ -499,14 +499,34 @@ namespace storm {
template<typename ValueType>
std::unique_ptr<CheckResult> SparseMdpPrctlHelper<ValueType>::computeConditionalProbabilities(OptimizationDirection dir, storm::storage::sparse::state_type initialState, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, storm::storage::SparseMatrix<ValueType> const& backwardTransitions, storm::storage::BitVector const& targetStates, storm::storage::BitVector const& conditionStates, bool qualitative, storm::utility::solver::MinMaxLinearEquationSolverFactory<ValueType> const& minMaxLinearEquationSolverFactory) {
// For the max-case, we can simply take the given target states. For the min-case, however, we need to
// find the MECs of non-target states and make them the new target states.
storm::storage::BitVector fixedTargetStates;
if (dir == OptimizationDirection::Maximize) {
fixedTargetStates = targetStates;
} else {
fixedTargetStates = storm::storage::BitVector(targetStates.size());
storm::storage::MaximalEndComponentDecomposition<ValueType> mecDecomposition(transitionMatrix, backwardTransitions, ~targetStates);
for (auto const& mec : mecDecomposition) {
for (auto const& stateActionsPair : mec) {
fixedTargetStates.set(stateActionsPair.first);
}
}
}
// We solve the max-case and later adjust the result if the optimization direction was to minimize.
// FIXME: actually do this.
storm::storage::BitVector initialStatesBitVector(transitionMatrix.getRowGroupCount());
initialStatesBitVector.set(initialState);
storm::storage::BitVector allStates(initialStatesBitVector.size(), true);
std::vector<ValueType> conditionProbabilities = std::move(computeUntilProbabilities(OptimizationDirection::Maximize, transitionMatrix, backwardTransitions, allStates, conditionStates, false, false, minMaxLinearEquationSolverFactory).result);
std::vector<ValueType> targetProbabilities = std::move(computeUntilProbabilities(OptimizationDirection::Maximize, transitionMatrix, backwardTransitions, allStates, targetStates, false, false, minMaxLinearEquationSolverFactory).result);
// If the conditional probability is undefined for the initial state, we return directly.
if (storm::utility::isZero(conditionProbabilities[initialState])) {
return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(initialState, storm::utility::infinity<ValueType>()));
}
std::vector<ValueType> targetProbabilities = std::move(computeUntilProbabilities(OptimizationDirection::Maximize, transitionMatrix, backwardTransitions, allStates, fixedTargetStates, false, false, minMaxLinearEquationSolverFactory).result);
storm::storage::BitVector statesWithProbabilityGreater0E(transitionMatrix.getRowGroupCount(), true);
storm::storage::sparse::state_type state = 0;
@ -517,16 +537,11 @@ namespace storm {
++state;
}
// If the conditional probability is undefined for the initial state, we return directly.
if (!statesWithProbabilityGreater0E.get(initialState)) {
return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(initialState, storm::utility::infinity<ValueType>()));
}
// Determine those states that need to be equipped with a restart mechanism.
storm::storage::BitVector problematicStates = storm::utility::graph::performProb0E(transitionMatrix, transitionMatrix.getRowGroupIndices(), backwardTransitions, allStates, conditionStates | targetStates);
storm::storage::BitVector problematicStates = storm::utility::graph::performProb0E(transitionMatrix, transitionMatrix.getRowGroupIndices(), backwardTransitions, allStates, conditionStates | fixedTargetStates);
// Otherwise, we build the transformed MDP.
storm::storage::BitVector relevantStates = storm::utility::graph::getReachableStates(transitionMatrix, initialStatesBitVector, allStates, conditionStates | targetStates);
storm::storage::BitVector relevantStates = storm::utility::graph::getReachableStates(transitionMatrix, initialStatesBitVector, allStates, conditionStates | fixedTargetStates);
std::vector<uint_fast64_t> numberOfStatesBeforeRelevantStates = relevantStates.getNumberOfSetBitsBeforeIndices();
storm::storage::sparse::state_type newGoalState = relevantStates.getNumberOfSetBits();
storm::storage::sparse::state_type newStopState = newGoalState + 1;
@ -537,7 +552,7 @@ namespace storm {
uint_fast64_t currentRow = 0;
for (auto state : relevantStates) {
builder.newRowGroup(currentRow);
if (targetStates.get(state)) {
if (fixedTargetStates.get(state)) {
builder.addNextValue(currentRow, newGoalState, conditionProbabilities[state]);
if (!storm::utility::isZero(conditionProbabilities[state])) {
builder.addNextValue(currentRow, newFailState, 1 - conditionProbabilities[state]);
@ -581,7 +596,7 @@ namespace storm {
storm::storage::SparseMatrix<ValueType> newBackwardTransitions = newTransitionMatrix.transpose(true);
std::vector<ValueType> goalProbabilities = std::move(computeUntilProbabilities(OptimizationDirection::Maximize, newTransitionMatrix, newBackwardTransitions, storm::storage::BitVector(newFailState + 1, true), newGoalStates, false, false, minMaxLinearEquationSolverFactory).result);
return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(initialState, goalProbabilities[numberOfStatesBeforeRelevantStates[initialState]]));
return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(initialState, dir == OptimizationDirection::Maximize ? goalProbabilities[numberOfStatesBeforeRelevantStates[initialState]] : storm::utility::one<ValueType>() - goalProbabilities[numberOfStatesBeforeRelevantStates[initialState]]));
}
template class SparseMdpPrctlHelper<double>;

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