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@ -200,7 +200,7 @@ namespace storm { |
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template <typename ValueType, typename RewardModelType> |
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template <typename ValueType, typename RewardModelType> |
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std::vector<ValueType> SparseMarkovAutomatonCslHelper::computeReachabilityRewards(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, storm::storage::SparseMatrix<ValueType> const& backwardTransitions, std::vector<ValueType> const& exitRateVector, storm::storage::BitVector const& markovianStates, RewardModelType const& rewardModel, storm::storage::BitVector const& psiStates, storm::solver::MinMaxLinearEquationSolverFactory<ValueType> const& minMaxLinearEquationSolverFactory) { |
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std::vector<ValueType> SparseMarkovAutomatonCslHelper::computeReachabilityRewards(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, storm::storage::SparseMatrix<ValueType> const& backwardTransitions, std::vector<ValueType> const& exitRateVector, storm::storage::BitVector const& markovianStates, RewardModelType const& rewardModel, storm::storage::BitVector const& psiStates, storm::solver::MinMaxLinearEquationSolverFactory<ValueType> const& minMaxLinearEquationSolverFactory) { |
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std::vector<ValueType> stateRewardWeights(transitionMatrix.getRowGroupCount()); |
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std::vector<ValueType> stateRewardWeights(transitionMatrix.getRowGroupCount(), storm::utility::zero<ValueType>()); |
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for (auto const markovianState : markovianStates) { |
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for (auto const markovianState : markovianStates) { |
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stateRewardWeights[markovianState] = storm::utility::one<ValueType>() / exitRateVector[markovianState]; |
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stateRewardWeights[markovianState] = storm::utility::one<ValueType>() / exitRateVector[markovianState]; |
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} |
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} |
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@ -382,10 +382,10 @@ namespace storm { |
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uint_fast64_t numberOfStates = transitionMatrix.getRowGroupCount(); |
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uint_fast64_t numberOfStates = transitionMatrix.getRowGroupCount(); |
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// First, we need to check which states have infinite expected time (by definition).
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// First, we need to check which states have infinite expected reward (by definition).
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storm::storage::BitVector infinityStates; |
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storm::storage::BitVector infinityStates; |
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if (dir == OptimizationDirection::Minimize) { |
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if (dir == OptimizationDirection::Minimize) { |
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// If we need to compute the minimum expected times, we have to set the values of those states to infinity that, under all schedulers,
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// If we need to compute the minimum expected rewards, we have to set the values of those states to infinity that, under all schedulers,
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// reach a bottom SCC without a goal state.
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// reach a bottom SCC without a goal state.
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// So we start by computing all bottom SCCs without goal states.
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// So we start by computing all bottom SCCs without goal states.
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@ -406,8 +406,7 @@ namespace storm { |
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infinityStates = storm::utility::graph::performProbGreater0A(transitionMatrix, |
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infinityStates = storm::utility::graph::performProbGreater0A(transitionMatrix, |
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transitionMatrix.getRowGroupIndices(), |
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transitionMatrix.getRowGroupIndices(), |
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backwardTransitions, |
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backwardTransitions, |
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storm::storage::BitVector( |
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numberOfStates, true), |
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~goalStates, |
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unionOfNonGoalBSccs); |
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unionOfNonGoalBSccs); |
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} else { |
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} else { |
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// Otherwise, we have no infinity states.
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// Otherwise, we have no infinity states.
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@ -432,8 +431,7 @@ namespace storm { |
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if (!unionOfNonGoalMaximalEndComponents.empty()) { |
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if (!unionOfNonGoalMaximalEndComponents.empty()) { |
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// Now we need to check for which states there exists a scheduler that reaches one of the previously computed states.
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// Now we need to check for which states there exists a scheduler that reaches one of the previously computed states.
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infinityStates = storm::utility::graph::performProbGreater0E(backwardTransitions, |
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infinityStates = storm::utility::graph::performProbGreater0E(backwardTransitions, |
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storm::storage::BitVector( |
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numberOfStates, true), |
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~goalStates, |
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unionOfNonGoalMaximalEndComponents); |
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unionOfNonGoalMaximalEndComponents); |
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} else { |
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} else { |
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// Otherwise, we have no infinity states.
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// Otherwise, we have no infinity states.
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@ -447,17 +445,27 @@ namespace storm { |
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std::vector<ValueType> result(numberOfStates); |
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std::vector<ValueType> result(numberOfStates); |
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if (!maybeStates.empty()) { |
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if (!maybeStates.empty()) { |
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// Then, we can eliminate the rows and columns for all states whose values are already known.
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// Then, we can eliminate the rows and columns for all states whose values are already known.
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std::vector<ValueType> x(maybeStates.getNumberOfSetBits()); |
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storm::storage::SparseMatrix<ValueType> submatrix = transitionMatrix.getSubmatrix(true, maybeStates, |
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maybeStates); |
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// Finally, prepare the actual right-hand side.
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std::vector<ValueType> b(submatrix.getRowCount()); |
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storm::utility::vector::selectVectorValues(b, maybeStates, |
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storm::storage::SparseMatrix<ValueType> submatrix; |
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std::vector<ValueType> b; |
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if (infinityStates.empty()) { |
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submatrix = transitionMatrix.getSubmatrix(true, maybeStates, maybeStates); |
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b.resize(submatrix.getRowCount()); |
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storm::utility::vector::selectVectorValues(b, maybeStates, |
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transitionMatrix.getRowGroupIndices(), |
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transitionMatrix.getRowGroupIndices(), |
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stateActionRewardVector); |
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stateActionRewardVector); |
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} else { |
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// If there are infinity states, we also have to eliminate the choices that lead from a maybe state to an infinity state
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storm::storage::BitVector selectedChoices = transitionMatrix.getRowFilter(maybeStates, ~infinityStates); |
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submatrix = transitionMatrix.getSubmatrix(false, selectedChoices, maybeStates); |
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b.resize(submatrix.getRowCount()); |
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storm::utility::vector::selectVectorValues(b, selectedChoices, stateActionRewardVector); |
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} |
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// Initialize the solution vector
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std::vector<ValueType> x(maybeStates.getNumberOfSetBits()); |
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// Solve the corresponding system of equations.
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// Solve the corresponding system of equations.
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std::unique_ptr<storm::solver::MinMaxLinearEquationSolver<ValueType>> solver = minMaxLinearEquationSolverFactory.create( |
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std::unique_ptr<storm::solver::MinMaxLinearEquationSolver<ValueType>> solver = minMaxLinearEquationSolverFactory.create( |
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submatrix); |
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submatrix); |
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