sp
/
tempest
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity
Browse Source

Use boost::bimap for the belief space <-> state space mapping

tempestpy_adaptions
Alexander Bork 5 years ago
parent
c64591ffb3
commit
8d3254b8d0
2 changed files with 23 additions and 20 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 36
      src/storm-pomdp/modelchecker/ApproximatePOMDPModelchecker.cpp
  2. 5
      src/storm-pomdp/modelchecker/ApproximatePOMDPModelchecker.h

36
src/storm-pomdp/modelchecker/ApproximatePOMDPModelchecker.cpp
View File

@ -2,7 +2,6 @@
#include <boost/algorithm/string.hpp>
#include "storm/utility/ConstantsComparator.h"
#include "storm/models/sparse/Dtmc.h"
#include "storm/models/sparse/StandardRewardModel.h"
@ -105,7 +104,7 @@ namespace storm {
boost::optional<std::map<uint64_t, ValueType>> overApproximationMap,
boost::optional<std::map<uint64_t, ValueType>> underApproximationMap) {
STORM_PRINT("Use On-The-Fly Grid Generation" << std::endl)
auto result = computeRefinementFirstStep(pomdp, targetObservations, min, observationResolutionVector, computeRewards, explorationThreshold, overApproximationMap,
auto result = computeFirstRefinementStep(pomdp, targetObservations, min, observationResolutionVector, computeRewards, explorationThreshold, overApproximationMap,
underApproximationMap);
return std::make_unique<POMDPCheckResult<ValueType>>(POMDPCheckResult<ValueType>{result->overApproxValue, result->underApproxValue});
}
@ -113,7 +112,7 @@ namespace storm {
template<typename ValueType, typename RewardModelType>
std::unique_ptr<RefinementComponents<ValueType>>
ApproximatePOMDPModelchecker<ValueType, RewardModelType>::computeRefinementFirstStep(storm::models::sparse::Pomdp<ValueType, RewardModelType> const &pomdp,
ApproximatePOMDPModelchecker<ValueType, RewardModelType>::computeFirstRefinementStep(storm::models::sparse::Pomdp<ValueType, RewardModelType> const &pomdp,
std::set<uint32_t> const &targetObservations, bool min,
std::vector<uint64_t> &observationResolutionVector,
bool computeRewards, double explorationThreshold,
@ -133,7 +132,7 @@ namespace storm {
//Use caching to avoid multiple computation of the subsimplices and lambdas
std::map<uint64_t, std::vector<std::vector<ValueType>>> subSimplexCache;
std::map<uint64_t, std::vector<ValueType>> lambdaCache;
std::map<uint64_t, uint64_t> beliefStateMap;
bsmap_type beliefStateMap;
std::deque<uint64_t> beliefsToBeExpanded;
@ -151,8 +150,7 @@ namespace storm {
beliefList.push_back(initialBelief);
beliefIsTarget.push_back(targetObservations.find(initialBelief.observation) != targetObservations.end());
// These are the components to build the MDP from the grid TODO make a better structure to allow for fast reverse lookups (state-->belief) as it is a bijective function (boost:bimap?)
// These are the components to build the MDP from the grid
// Reserve states 0 and 1 as always sink/goal states
std::vector<std::vector<std::map<uint64_t, ValueType>>> mdpTransitions = {{{{0, storm::utility::one<ValueType>()}}},
{{{1, storm::utility::one<ValueType>()}}}};
@ -161,7 +159,7 @@ namespace storm {
std::vector<uint64_t> targetStates = {1};
uint64_t mdpStateId = 2;
beliefStateMap[initialBelief.id] = mdpStateId;
beliefStateMap.insert(bsmap_type::value_type(initialBelief.id, mdpStateId));
++mdpStateId;
// Map to save the weighted values resulting from the preprocessing for the beliefs / indices in beliefSpace
@ -225,7 +223,7 @@ namespace storm {
hintVector.push_back(targetObservations.find(initialBelief.observation) != targetObservations.end() ? storm::utility::one<ValueType>()
: storm::utility::zero<ValueType>());
beliefStateMap[nextId] = mdpStateId;
beliefStateMap.insert(bsmap_type::value_type(nextId, mdpStateId));
initTransitionInActionBelief[mdpStateId] = initLambdas[j];
++nextId;
++mdpStateId;
@ -261,9 +259,9 @@ namespace storm {
// Depending on whether we compute rewards, we select the right initial result
// MDP stuff
std::vector<std::map<uint64_t, ValueType>> transitionsInBelief;
targetStates.push_back(beliefStateMap[currId]);
targetStates.push_back(beliefStateMap.left.at(currId));
std::map<uint64_t, ValueType> transitionInActionBelief;
transitionInActionBelief[beliefStateMap[currId]] = storm::utility::one<ValueType>();
transitionInActionBelief[beliefStateMap.left.at(currId)] = storm::utility::one<ValueType>();
transitionsInBelief.push_back(transitionInActionBelief);
mdpTransitions.push_back(transitionsInBelief);
} else {
@ -332,12 +330,13 @@ namespace storm {
: storm::utility::zero<ValueType>());
}
beliefsToBeExpanded.push_back(nextId);
beliefStateMap[nextId] = mdpStateId;
beliefStateMap.insert(bsmap_type::value_type(nextId, mdpStateId));
transitionInActionBelief[mdpStateId] = iter->second * lambdas[j];
++nextId;
++mdpStateId;
} else {
transitionInActionBelief[beliefStateMap[getBeliefIdInVector(beliefGrid, observation, subSimplex[j])]] = iter->second * lambdas[j];
transitionInActionBelief[beliefStateMap.left.at(getBeliefIdInVector(beliefGrid, observation, subSimplex[j]))] =
iter->second * lambdas[j];
}
}
}
@ -361,7 +360,7 @@ namespace storm {
if (transitionsInBelief.empty()) {
std::map<uint64_t, ValueType> transitionInActionBelief;
transitionInActionBelief[beliefStateMap[currId]] = storm::utility::one<ValueType>();
transitionInActionBelief[beliefStateMap.left.at(currId)] = storm::utility::one<ValueType>();
transitionsInBelief.push_back(transitionInActionBelief);
}
mdpTransitions.push_back(transitionsInBelief);
@ -374,7 +373,7 @@ namespace storm {
storm::models::sparse::StateLabeling mdpLabeling(mdpTransitions.size());
mdpLabeling.addLabel("init");
mdpLabeling.addLabel("target");
mdpLabeling.addLabelToState("init", beliefStateMap[initialBelief.id]);
mdpLabeling.addLabelToState("init", beliefStateMap.left.at(initialBelief.id));
for (auto targetState : targetStates) {
mdpLabeling.addLabelToState("target", targetState);
}
@ -382,7 +381,7 @@ namespace storm {
storm::models::sparse::Mdp<ValueType, RewardModelType> overApproxMdp(modelComponents);
if (computeRewards) {
storm::models::sparse::StandardRewardModel<ValueType> mdpRewardModel(boost::none, std::vector<ValueType>(modelComponents.transitionMatrix.getRowCount()));
for (auto const &iter : beliefStateMap) {
for (auto const &iter : beliefStateMap.left) {
auto currentBelief = beliefList[iter.first];
auto representativeState = pomdp.getStatesWithObservation(currentBelief.observation).front();
for (uint64_t action = 0; action < overApproxMdp.getNumberOfChoices(iter.second); ++action) {
@ -415,7 +414,7 @@ namespace storm {
STORM_LOG_ASSERT(res, "Result not exist.");
res->filter(storm::modelchecker::ExplicitQualitativeCheckResult(storm::storage::BitVector(overApproxMdp.getNumberOfStates(), true)));
auto overApproxResultMap = res->asExplicitQuantitativeCheckResult<ValueType>().getValueMap();
auto overApprox = overApproxResultMap[beliefStateMap[initialBelief.id]];
auto overApprox = overApproxResultMap[beliefStateMap.left.at(initialBelief.id)];
STORM_PRINT("Time Overapproximation: " << overApproxTimer << std::endl)
auto underApprox = weightedSumUnderMap[initialBelief.id];
@ -423,9 +422,10 @@ namespace storm {
STORM_PRINT("Under-Approximation Result: " << underApprox << std::endl);
// Transfer the underapproximation results from the belief id space to the MDP id space
std::map<uint64_t, ValueType> underApproxResultMap;
std::map<uint64_t, ValueType> underApproxResultMap = {{0, storm::utility::zero<ValueType>()},
{1, storm::utility::one<ValueType>()}};
for (auto const &belief : beliefGrid) {
underApproxResultMap[beliefStateMap[belief.id]] = weightedSumUnderMap[belief.id];
underApproxResultMap[beliefStateMap.left.at(belief.id)] = weightedSumUnderMap[belief.id];
}
return std::make_unique<RefinementComponents<ValueType>>(

5
src/storm-pomdp/modelchecker/ApproximatePOMDPModelchecker.h
View File

@ -3,12 +3,15 @@
#include "storm/models/sparse/Pomdp.h"
#include "storm/utility/logging.h"
#include "storm-pomdp/storage/Belief.h"
#include <boost/bimap.hpp>
#include "storm/storage/jani/Property.h"
namespace storm {
namespace pomdp {
namespace modelchecker {
typedef boost::bimap<uint64_t, uint64_t> bsmap_type;
template<class ValueType>
struct POMDPCheckResult {
ValueType overApproxValue;
@ -73,7 +76,7 @@ namespace storm {
* @return
*/
std::unique_ptr<RefinementComponents<ValueType>>
computeRefinementFirstStep(storm::models::sparse::Pomdp<ValueType, RewardModelType> const &pomdp,
computeFirstRefinementStep(storm::models::sparse::Pomdp<ValueType, RewardModelType> const &pomdp,
std::set<uint32_t> const &targetObservations, bool min, std::vector<uint64_t> &observationResolutionVector,
bool computeRewards, double explorationThreshold, boost::optional<std::map<uint64_t, ValueType>> overApproximationMap = boost::none,
boost::optional<std::map<uint64_t, ValueType>> underApproximationMap = boost::none);

Write Preview
Loading…
Cancel
Save