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Added generation of an MDP for the over-approximation in the on-the-fly state exploration

tempestpy_adaptions
Alexander Bork 5 years ago
parent
bbd3ec7287
commit
c663edbd85
1 changed files with 82 additions and 14 deletions
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  1. 96
      src/storm-pomdp/modelchecker/ApproximatePOMDPModelchecker.cpp

96
src/storm-pomdp/modelchecker/ApproximatePOMDPModelchecker.cpp
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@ -81,6 +81,15 @@ namespace storm {
beliefIsTarget.push_back(
targetObservations.find(initialBelief.observation) != targetObservations.end());
// These are the components to build the MDP from the grid
std::map<uint64_t, uint64_t> beliefStateMap;
std::vector<std::vector<std::map<uint64_t, ValueType>>> mdpTransitions;
std::vector<uint64_t> targetStates;
uint64_t mdpStateId = 0;
beliefStateMap[initialBelief.id] = mdpStateId;
++mdpStateId;
// for the initial belief, add the triangulated initial states
std::pair<std::vector<std::vector<ValueType>>, std::vector<ValueType>> initTemp = computeSubSimplexAndLambdas(
initialBelief.probabilities, gridResolution);
@ -90,6 +99,8 @@ namespace storm {
lambdaCache[0] = initLambdas;
bool initInserted = false;
std::vector<std::map<uint64_t, ValueType>> initTransitionsInBelief;
std::map<uint64_t, ValueType> initTransitionInActionBelief;
for (size_t j = 0; j < initLambdas.size(); ++j) {
if (!cc.isEqual(initLambdas[j], storm::utility::zero<ValueType>())) {
@ -107,12 +118,21 @@ namespace storm {
beliefGrid.push_back(gridBelief);
beliefIsTarget.push_back(targetObservations.find(initialBelief.observation) != targetObservations.end());
beliefsToBeExpanded.push_back(nextId);
beliefStateMap[nextId] = mdpStateId;
initTransitionInActionBelief[mdpStateId] = initLambdas[j];
++nextId;
++mdpStateId;
}
}
}
}
// If the initial belief is not on the grid, we add the transitions from our initial MDP state to the triangulated beliefs
if (!initTransitionInActionBelief.empty()) {
initTransitionsInBelief.push_back(initTransitionInActionBelief);
mdpTransitions.push_back(initTransitionsInBelief);
}
//beliefsToBeExpanded.push_back(initialBelief.id); TODO I'm curious what happens if we do this instead of first triangulating. Should do nothing special if belief is on grid, otherwise it gets interesting
@ -124,6 +144,14 @@ namespace storm {
if (isTarget) {
result.emplace(std::make_pair(currId, storm::utility::one<ValueType>()));
result_backup.emplace(std::make_pair(currId, storm::utility::one<ValueType>()));
// MDP stuff
std::vector<std::map<uint64_t, ValueType>> transitionsInBelief;
targetStates.push_back(beliefStateMap[currId]);
std::map<uint64_t, ValueType> transitionInActionBelief;
transitionInActionBelief[beliefStateMap[currId]] = storm::utility::one<ValueType>();
transitionsInBelief.push_back(transitionInActionBelief);
mdpTransitions.push_back(transitionsInBelief);
} else {
result.emplace(std::make_pair(currId, storm::utility::zero<ValueType>()));
result_backup.emplace(std::make_pair(currId, storm::utility::zero<ValueType>()));
@ -131,12 +159,14 @@ namespace storm {
uint64_t numChoices = pomdp.getNumberOfChoices(pomdp.getStatesWithObservation(beliefList[currId].observation).front());
std::vector<std::map<uint32_t, ValueType>> observationProbabilitiesInAction(numChoices);
std::vector<std::map<uint32_t, uint64_t>> nextBelievesInAction(numChoices);
std::vector<std::map<uint64_t, ValueType>> transitionsInBelief;
for (uint64_t action = 0; action < numChoices; ++action) {
std::map<uint32_t, ValueType> actionObservationProbabilities = computeObservationProbabilitiesAfterAction(pomdp, beliefList[currId], action);
std::map<uint32_t, uint64_t> actionObservationBelieves;
for (auto iter = actionObservationProbabilities.begin();
iter != actionObservationProbabilities.end(); ++iter) {
std::map<uint64_t, ValueType> transitionInActionBelief;
for (auto iter = actionObservationProbabilities.begin(); iter != actionObservationProbabilities.end(); ++iter) {
uint32_t observation = iter->first;
// THIS CALL IS SLOW
// TODO speed this up
@ -159,7 +189,6 @@ namespace storm {
subSimplexCache[idNextBelief] = subSimplex;
lambdaCache[idNextBelief] = lambdas;
}
for (size_t j = 0; j < lambdas.size(); ++j) {
if (!cc.isEqual(lambdas[j], storm::utility::zero<ValueType>())) {
if (getBeliefIdInVector(beliefGrid, observation, subSimplex[j]) == uint64_t(-1)) {
@ -169,17 +198,31 @@ namespace storm {
beliefGrid.push_back(gridBelief);
beliefIsTarget.push_back(targetObservations.find(observation) != targetObservations.end());
beliefsToBeExpanded.push_back(nextId);
beliefStateMap[nextId] = mdpStateId;
transitionInActionBelief[mdpStateId] = iter->second * lambdas[j];
++nextId;
++mdpStateId;
} else {
transitionInActionBelief[beliefStateMap[getBeliefIdInVector(beliefGrid, observation, subSimplex[j])]] = iter->second * lambdas[j];
}
}
}
}
observationProbabilitiesInAction[action] = actionObservationProbabilities;
nextBelievesInAction[action] = actionObservationBelieves;
if (!transitionInActionBelief.empty()) {
transitionsInBelief.push_back(transitionInActionBelief);
}
}
observationProbabilities.emplace(
std::make_pair(currId, observationProbabilitiesInAction));
observationProbabilities.emplace(std::make_pair(currId, observationProbabilitiesInAction));
nextBelieves.emplace(std::make_pair(currId, nextBelievesInAction));
if (transitionsInBelief.empty()) {
std::map<uint64_t, ValueType> transitionInActionBelief;
transitionInActionBelief[beliefStateMap[currId]] = storm::utility::one<ValueType>();
transitionsInBelief.push_back(transitionInActionBelief);
}
mdpTransitions.push_back(transitionsInBelief);
}
}
expansionTimer.stop();
@ -187,6 +230,18 @@ namespace storm {
STORM_PRINT("#Believes in List: " << beliefList.size() << std::endl)
STORM_PRINT("Belief space expansion took " << expansionTimer << std::endl)
storm::models::sparse::StateLabeling mdpLabeling(mdpTransitions.size());
mdpLabeling.addLabel("init");
mdpLabeling.addLabel("target");
mdpLabeling.addLabelToState("init", 0);
for (auto targetState : targetStates) {
mdpLabeling.addLabelToState("target", targetState);
}
storm::storage::sparse::ModelComponents<ValueType, RewardModelType> modelComponents(buildTransitionMatrix(mdpTransitions), mdpLabeling);
storm::models::sparse::Mdp<ValueType, RewardModelType> overApproxMdp(modelComponents);
overApproxMdp.printModelInformationToStream(std::cout);
storm::utility::Stopwatch overApproxTimer(true);
// Value Iteration
while (!finished && iteration < maxIterations) {
@ -276,21 +331,34 @@ namespace storm {
}
overApproxTimer.stop();
storm::utility::Stopwatch underApproxTimer(true);
ValueType underApprox = storm::utility::zero<ValueType>();
/*storm::utility::Stopwatch underApproxTimer(true);
ValueType underApprox = computeUnderapproximationWithMDP(pomdp, beliefList, beliefIsTarget, targetObservations, observationProbabilities, nextBelieves,
result, chosenActions, gridResolution, initialBelief.id, min, false);
underApproxTimer.stop();
underApproxTimer.stop();*/
STORM_PRINT("Time Overapproximation: " << overApproxTimer
<< std::endl
<< "Time Underapproximation: " << underApproxTimer
<< std::endl);
// STORM_PRINT("Time Overapproximation: " << overApproxTimer << std::endl << "Time Underapproximation: " << underApproxTimer << std::endl);
STORM_PRINT("Over-Approximation Result: " << overApprox << std::endl);
STORM_PRINT("Under-Approximation Result: " << underApprox << std::endl);
//STORM_PRINT("Under-Approximation Result: " << underApprox << std::endl);
return std::make_unique<POMDPCheckResult<ValueType>>(
POMDPCheckResult<ValueType>{overApprox, underApprox});
auto model = std::make_shared<storm::models::sparse::Mdp<ValueType, RewardModelType>>(overApproxMdp);
auto modelPtr = std::static_pointer_cast<storm::models::sparse::Model<ValueType, RewardModelType>>(model);
std::vector<std::string> parameterNames;
storm::api::exportSparseModelAsDrn(modelPtr, "test", parameterNames);
std::string propertyString = min ? "Pmin=? [F \"target\"]" : "Pmax=? [F \"target\"]";
std::vector<storm::jani::Property> propertyVector = storm::api::parseProperties(propertyString);
std::shared_ptr<storm::logic::Formula const> property = storm::api::extractFormulasFromProperties(propertyVector).front();
std::unique_ptr<storm::modelchecker::CheckResult> res(storm::api::verifyWithSparseEngine<ValueType>(model, storm::api::createTask<ValueType>(property, true)));
STORM_LOG_ASSERT(res, "Result not exist.");
res->filter(storm::modelchecker::ExplicitQualitativeCheckResult(model->getInitialStates()));
STORM_PRINT("OverApprox MDP: " << (res->asExplicitQuantitativeCheckResult<ValueType>().getValueMap().begin()->second) << std::endl);
return std::make_unique<POMDPCheckResult<ValueType>>(POMDPCheckResult<ValueType>{overApprox, underApprox});
}

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