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BaierUpperRewardBoundsComputer: Added a function to get an upper bound for the expected number of visits of each state.

tempestpy_adaptions
Tim Quatmann 6 years ago
parent
commit
7ab409fd2a
  1. 35
      src/storm/modelchecker/prctl/helper/BaierUpperRewardBoundsComputer.cpp
  2. 14
      src/storm/modelchecker/prctl/helper/BaierUpperRewardBoundsComputer.h

35
src/storm/modelchecker/prctl/helper/BaierUpperRewardBoundsComputer.cpp

@ -13,15 +13,12 @@ namespace storm {
namespace helper {
template<typename ValueType>
BaierUpperRewardBoundsComputer<ValueType>::BaierUpperRewardBoundsComputer(storm::storage::SparseMatrix<ValueType> const& transitionMatrix, std::vector<ValueType> const& rewards, std::vector<ValueType> const& oneStepTargetProbabilities) : transitionMatrix(transitionMatrix), rewards(rewards), oneStepTargetProbabilities(oneStepTargetProbabilities) {
BaierUpperRewardBoundsComputer<ValueType>::BaierUpperRewardBoundsComputer(storm::storage::SparseMatrix<ValueType> const& transitionMatrix, std::vector<ValueType> const& rewards, std::vector<ValueType> const& oneStepTargetProbabilities) : _transitionMatrix(transitionMatrix), _rewards(rewards), _oneStepTargetProbabilities(oneStepTargetProbabilities) {
// Intentionally left empty.
}
template<typename ValueType>
ValueType BaierUpperRewardBoundsComputer<ValueType>::computeUpperBound() {
STORM_LOG_TRACE("Computing upper reward bounds using variant-2 of Baier et al.");
std::chrono::high_resolution_clock::time_point start = std::chrono::high_resolution_clock::now();
std::vector<ValueType> BaierUpperRewardBoundsComputer<ValueType>::computeUpperBoundOnExpectedVisitingTimes(storm::storage::SparseMatrix<ValueType> const& transitionMatrix, std::vector<ValueType> const& oneStepTargetProbabilities) {
std::vector<uint64_t> stateToScc(transitionMatrix.getRowGroupCount());
{
// Start with an SCC decomposition of the system.
@ -106,18 +103,28 @@ namespace storm {
remainingStates.set(newStates.begin(), newStates.end(), false);
newStates.clear();
}
for (uint64_t state = 0; state < result.size(); ++state) {
ValueType maxReward = storm::utility::zero<ValueType>();
for (auto row = transitionMatrix.getRowGroupIndices()[state], endRow = transitionMatrix.getRowGroupIndices()[state + 1]; row < endRow; ++row) {
maxReward = std::max(maxReward, rewards[row]);
}
result[state] = storm::utility::one<ValueType>() / result[state] * maxReward;
// Transform the d_t to an upper bound for zeta(t)
for (auto& r : result) {
r = storm::utility::one<ValueType>() / r;
}
return result;
}
template<typename ValueType>
ValueType BaierUpperRewardBoundsComputer<ValueType>::computeUpperBound() {
STORM_LOG_TRACE("Computing upper reward bounds using variant-2 of Baier et al.");
std::chrono::high_resolution_clock::time_point start = std::chrono::high_resolution_clock::now();
auto expVisits = computeUpperBoundOnExpectedVisitingTimes(_transitionMatrix, _oneStepTargetProbabilities);
ValueType upperBound = storm::utility::zero<ValueType>();
for (auto const& e : result) {
upperBound += e;
for (uint64_t state = 0; state < expVisits.size(); ++state) {
ValueType maxReward = storm::utility::zero<ValueType>();
for (auto row = _transitionMatrix.getRowGroupIndices()[state], endRow = _transitionMatrix.getRowGroupIndices()[state + 1]; row < endRow; ++row) {
maxReward = std::max(maxReward, _rewards[row]);
}
upperBound += expVisits[state] * maxReward;
}
STORM_LOG_TRACE("Baier algorithm for reward bound computation (variant 2) computed bound " << upperBound << ".");

14
src/storm/modelchecker/prctl/helper/BaierUpperRewardBoundsComputer.h

@ -29,10 +29,18 @@ namespace storm {
*/
ValueType computeUpperBound();
/*!
* Computes for each state an upper bound for the maximal expected times each state is visited.
* @param transitionMatrix The matrix defining the transitions of the system without the transitions
* that lead directly to the goal state.
* @param oneStepTargetProbabilities For each choice the probability to go to a goal state in one step.
*/
static std::vector<ValueType> computeUpperBoundOnExpectedVisitingTimes(storm::storage::SparseMatrix<ValueType> const& transitionMatrix, std::vector<ValueType> const& oneStepTargetProbabilities);
private:
storm::storage::SparseMatrix<ValueType> const& transitionMatrix;
std::vector<ValueType> const& rewards;
std::vector<ValueType> const& oneStepTargetProbabilities;
storm::storage::SparseMatrix<ValueType> const& _transitionMatrix;
std::vector<ValueType> const& _rewards;
std::vector<ValueType> const& _oneStepTargetProbabilities;
};
}
}

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