Browse Source

No rewards for target states

Former-commit-id: 98e0139840
tempestpy_adaptions
Mavo 9 years ago
parent
commit
62f7305bea
  1. 17
      src/modelchecker/csl/helper/SparseCtmcCslHelper.cpp

17
src/modelchecker/csl/helper/SparseCtmcCslHelper.cpp

@ -651,15 +651,24 @@ namespace storm {
template <typename ValueType>
std::vector<ValueType> SparseCtmcCslHelper<ValueType>::computeExpectedTimes(storm::storage::SparseMatrix<ValueType> const& rateMatrix, storm::storage::SparseMatrix<ValueType> const& backwardTransitions, std::vector<ValueType> const& exitRateVector, storm::storage::BitVector const& initialStates, storm::storage::BitVector const& targetStates, bool qualitative/*, storm::utility::solver::LinearEquationSolverFactory<ValueType> const& linearEquationSolverFactory*/) {
// Compute expected time on CTMC by reduction to DTMC with rewards
// Compute expected time on CTMC by reduction to DTMC with rewards.
storm::storage::SparseMatrix<ValueType> probabilityMatrix = computeProbabilityMatrix(rateMatrix, exitRateVector);
// Initialize rewards.
std::vector<ValueType> totalRewardVector;
for (auto exitRate : exitRateVector) {
totalRewardVector.push_back(storm::utility::one<ValueType>() / exitRate);
for (size_t i = 0; i < exitRateVector.size(); ++i) {
std::cout << i << std::endl;
if (targetStates[i]) {
// Set reward for target states to 0.
totalRewardVector.push_back(storm::utility::zero<ValueType>());
} else {
// Reward is (1 / exitRate).
totalRewardVector.push_back(storm::utility::one<ValueType>() / exitRateVector[i]);
}
}
return storm::modelchecker::SparseDtmcEliminationModelChecker<storm::models::sparse::Dtmc<ValueType>>::computeReachabilityRewards(probabilityMatrix, backwardTransitions, initialStates, targetStates, totalRewardVector, false, qualitative);
// Enable again, if RationalFunction finally is supported
// Enable again, if RationalFunction finally is supported.
//return storm::modelchecker::helper::SparseDtmcPrctlHelper<ValueType>::computeReachabilityRewards(probabilityMatrix, backwardTransitions, totalRewardVector, targetStates, qualitative, linearEquationSolverFactory);
}

Loading…
Cancel
Save