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

Refactoring to include a list of all generated beliefs

tempestpy_adaptions
Alexander Bork 5 years ago
parent
74cfecd011
commit
2bc79e6e07
3 changed files with 180 additions and 87 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Unified View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 208
      src/storm-pomdp/modelchecker/ApproximatePOMDPModelchecker.cpp
  2. 35
      src/storm-pomdp/modelchecker/ApproximatePOMDPModelchecker.h
  3. 12
      src/storm-pomdp/storage/Belief.h

208
src/storm-pomdp/modelchecker/ApproximatePOMDPModelchecker.cpp
View File

@ -20,17 +20,26 @@ namespace storm {
bool finished = false; bool finished = false;
uint64_t iteration = 0; uint64_t iteration = 0;
std::vector<storm::pomdp::Belief<ValueType>> beliefList;
uint64_t nextId = 0;
// Initial belief always has ID 0
storm::pomdp::Belief<ValueType> initialBelief = getInitialBelief(pomdp, nextId);
++nextId;
beliefList.push_back(initialBelief);
std::vector<Belief<ValueType>> beliefGrid;
std::vector<storm::pomdp::Belief<ValueType>> beliefGrid;
std::vector<bool> beliefIsKnown; std::vector<bool> beliefIsKnown;
constructBeliefGrid(pomdp, target_observations, gridResolution, beliefGrid, beliefIsKnown);
constructBeliefGrid(pomdp, target_observations, gridResolution, beliefList, beliefGrid, beliefIsKnown,
nextId);
nextId = beliefList.size();
std::map<uint64_t, ValueType> result; std::map<uint64_t, ValueType> result;
std::map<uint64_t, ValueType> result_backup; std::map<uint64_t, ValueType> result_backup;
std::map<uint64_t, uint64_t> chosenActions;
std::vector<std::vector<std::map<uint32_t, ValueType>>> observationProbabilities; std::vector<std::vector<std::map<uint32_t, ValueType>>> observationProbabilities;
std::vector<std::vector<std::map<uint32_t, Belief<ValueType>>>> nextBelieves;
std::vector<std::vector<std::map<uint32_t, uint64_t>>> nextBelieves;
uint64_t nextId = beliefGrid.size();
for (size_t i = 0; i < beliefGrid.size(); ++i) { for (size_t i = 0; i < beliefGrid.size(); ++i) {
auto currentBelief = beliefGrid[i]; auto currentBelief = beliefGrid[i];
bool isTarget = beliefIsKnown[i]; bool isTarget = beliefIsKnown[i];
@ -42,23 +51,24 @@ namespace storm {
result_backup.emplace(std::make_pair(currentBelief.id, storm::utility::zero<ValueType>())); result_backup.emplace(std::make_pair(currentBelief.id, storm::utility::zero<ValueType>()));
std::vector<std::map<uint32_t, ValueType>> observationProbabilitiesInAction; std::vector<std::map<uint32_t, ValueType>> observationProbabilitiesInAction;
std::vector<std::map<uint32_t, Belief<ValueType>>> nextBelievesInAction;
std::vector<std::map<uint32_t, uint64_t>> nextBelievesInAction;
uint64_t numChoices = pomdp.getNumberOfChoices( uint64_t numChoices = pomdp.getNumberOfChoices(
pomdp.getStatesWithObservation(currentBelief.observation).front()); pomdp.getStatesWithObservation(currentBelief.observation).front());
for (uint64_t action = 0; action < numChoices; ++action) { for (uint64_t action = 0; action < numChoices; ++action) {
std::map<uint32_t, ValueType> actionObservationProbabilities = computeObservationProbabilitiesAfterAction( std::map<uint32_t, ValueType> actionObservationProbabilities = computeObservationProbabilitiesAfterAction(
pomdp, currentBelief, action); pomdp, currentBelief, action);
std::map<uint32_t, Belief<ValueType>> actionObservationBelieves;
std::map<uint32_t, uint64_t> actionObservationBelieves;
for (auto iter = actionObservationProbabilities.begin(); for (auto iter = actionObservationProbabilities.begin();
iter != actionObservationProbabilities.end(); ++iter) { iter != actionObservationProbabilities.end(); ++iter) {
uint32_t observation = iter->first; uint32_t observation = iter->first;
actionObservationBelieves[observation] = getBeliefAfterActionAndObservation(pomdp, actionObservationBelieves[observation] = getBeliefAfterActionAndObservation(pomdp,
beliefList,
currentBelief, currentBelief,
action, action,
observation, observation,
nextId); nextId);
++nextId;
nextId = beliefList.size();
} }
observationProbabilitiesInAction.push_back(actionObservationProbabilities); observationProbabilitiesInAction.push_back(actionObservationProbabilities);
nextBelievesInAction.push_back(actionObservationBelieves); nextBelievesInAction.push_back(actionObservationBelieves);
@ -67,24 +77,18 @@ namespace storm {
nextBelieves.push_back(nextBelievesInAction); nextBelieves.push_back(nextBelievesInAction);
} }
} }
STORM_LOG_DEBUG("End of Section 1");
// Value Iteration // Value Iteration
auto cc = storm::utility::ConstantsComparator<ValueType>(); auto cc = storm::utility::ConstantsComparator<ValueType>();
while (!finished && iteration < maxIterations) { while (!finished && iteration < maxIterations) {
STORM_PRINT("Iteration " << std::to_string(iteration) << std::endl);
STORM_LOG_DEBUG("Iteration " << iteration + 1);
bool improvement = false; bool improvement = false;
for (size_t i = 0; i < beliefGrid.size(); ++i) { for (size_t i = 0; i < beliefGrid.size(); ++i) {
bool isTarget = beliefIsKnown[i]; bool isTarget = beliefIsKnown[i];
if (!isTarget) { if (!isTarget) {
Belief<ValueType> currentBelief = beliefGrid[i];
STORM_LOG_DEBUG(
"Check Belief " << currentBelief.id << ": ||" << currentBelief.observation << "|"
<< currentBelief.probabilities << "||");
storm::pomdp::Belief<ValueType> currentBelief = beliefGrid[i];
// we can take any state with the observation as they have the same number of choices // we can take any state with the observation as they have the same number of choices
uint64_t numChoices = pomdp.getNumberOfChoices( uint64_t numChoices = pomdp.getNumberOfChoices(
pomdp.getStatesWithObservation(currentBelief.observation).front()); pomdp.getStatesWithObservation(currentBelief.observation).front());
STORM_LOG_DEBUG("Number choices: " << std::to_string(numChoices));
// Initialize the values for the value iteration // Initialize the values for the value iteration
ValueType chosenValue = min ? storm::utility::infinity<ValueType>() ValueType chosenValue = min ? storm::utility::infinity<ValueType>()
: -storm::utility::infinity<ValueType>(); : -storm::utility::infinity<ValueType>();
@ -96,8 +100,7 @@ namespace storm {
for (auto iter = observationProbabilities[i][action].begin(); for (auto iter = observationProbabilities[i][action].begin();
iter != observationProbabilities[i][action].end(); ++iter) { iter != observationProbabilities[i][action].end(); ++iter) {
uint32_t observation = iter->first; uint32_t observation = iter->first;
Belief<ValueType> nextBelief = nextBelieves[i][action][observation];
storm::pomdp::Belief<ValueType> nextBelief = beliefList[nextBelieves[i][action][observation]];
// compute subsimplex and lambdas according to the Lovejoy paper to approximate the next belief // compute subsimplex and lambdas according to the Lovejoy paper to approximate the next belief
std::pair<std::vector<std::vector<ValueType>>, std::vector<ValueType>> temp = computeSubSimplexAndLambdas( std::pair<std::vector<std::vector<ValueType>>, std::vector<ValueType>> temp = computeSubSimplexAndLambdas(
nextBelief.probabilities, gridResolution); nextBelief.probabilities, gridResolution);
@ -108,7 +111,7 @@ namespace storm {
for (size_t j = 0; j < lambdas.size(); ++j) { for (size_t j = 0; j < lambdas.size(); ++j) {
if (lambdas[j] != storm::utility::zero<ValueType>()) { if (lambdas[j] != storm::utility::zero<ValueType>()) {
sum += lambdas[j] * result_backup.at( sum += lambdas[j] * result_backup.at(
getBeliefIdInGrid(beliefGrid, observation, subSimplex[j]));
getBeliefIdInVector(beliefGrid, observation, subSimplex[j]));
} }
} }
currentValue += iter->second * sum; currentValue += iter->second * sum;
@ -124,22 +127,12 @@ namespace storm {
// TODO tie breaker? // TODO tie breaker?
} }
result[currentBelief.id] = chosenValue; result[currentBelief.id] = chosenValue;
chosenActions[currentBelief.id] = chosenActionIndex;
// Check if the iteration brought an improvement // Check if the iteration brought an improvement
if ((min && cc.isLess(storm::utility::zero<ValueType>(), if ((min && cc.isLess(storm::utility::zero<ValueType>(),
result_backup[currentBelief.id] - result[currentBelief.id])) || result_backup[currentBelief.id] - result[currentBelief.id])) ||
(!min && cc.isLess(storm::utility::zero<ValueType>(), (!min && cc.isLess(storm::utility::zero<ValueType>(),
result[currentBelief.id] - result_backup[currentBelief.id]))) { result[currentBelief.id] - result_backup[currentBelief.id]))) {
if (min) {
STORM_PRINT("Old: " << result_backup[currentBelief.id] << ", New: "
<< result[currentBelief.id] << std::endl << "Delta: "
<< result_backup[currentBelief.id] - result[currentBelief.id]
<< std::endl);
} else {
STORM_PRINT("Old: " << result_backup[currentBelief.id] << ", New: "
<< result[currentBelief.id] << std::endl << "Delta: "
<< result_backup[currentBelief.id] - result[currentBelief.id]
<< std::endl);
}
improvement = true; improvement = true;
} }
} }
@ -152,32 +145,120 @@ namespace storm {
++iteration; ++iteration;
} }
// maybe change this so the initial Belief always has ID 0
Belief<ValueType> initialBelief = getInitialBelief(pomdp, nextId);
++nextId;
STORM_PRINT("Grid approximation took " << iteration << " iterations" << std::endl);
beliefGrid.push_back(initialBelief);
beliefIsKnown.push_back(
target_observations.find(initialBelief.observation) != target_observations.end());
std::pair<std::vector<std::vector<ValueType>>, std::vector<ValueType>> temp = computeSubSimplexAndLambdas( std::pair<std::vector<std::vector<ValueType>>, std::vector<ValueType>> temp = computeSubSimplexAndLambdas(
initialBelief.probabilities, gridResolution); initialBelief.probabilities, gridResolution);
std::vector<std::vector<ValueType>> initSubSimplex = temp.first;
std::vector<ValueType> initLambdas = temp.second;
auto overApprox = storm::utility::zero<ValueType>();
for (size_t j = 0; j < initLambdas.size(); ++j) {
if (initLambdas[j] != storm::utility::zero<ValueType>()) {
overApprox += initLambdas[j] *
result_backup[getBeliefIdInVector(beliefGrid, initialBelief.observation,
initSubSimplex[j])];
}
}
// Now onto the under-approximation
/* All this has to be put into a separate function as we have to repeat it for other believes not in the grid
// first compute some things for the initial belief
std::vector<std::map<uint32_t, ValueType>> observationProbabilitiesInAction;
std::vector<std::map<uint32_t, uint64_t>> nextBelievesInAction;
uint64_t initialNumChoices = pomdp.getNumberOfChoices(
pomdp.getStatesWithObservation(initialBelief.observation).front());
for (uint64_t action = 0; action < initialNumChoices; ++action) {
std::map<uint32_t, ValueType> actionObservationProbabilities = computeObservationProbabilitiesAfterAction(
pomdp, initialBelief, action);
std::map<uint32_t, uint64_t> actionObservationBelieves;
for (auto iter = actionObservationProbabilities.begin();
iter != actionObservationProbabilities.end(); ++iter) {
uint32_t observation = iter->first;
actionObservationBelieves[observation] = getBeliefAfterActionAndObservation(pomdp,
beliefList,
initialBelief,
action,
observation,
nextId);
}
observationProbabilitiesInAction.push_back(actionObservationProbabilities);
nextBelievesInAction.push_back(actionObservationBelieves);
}
observationProbabilities.push_back(observationProbabilitiesInAction);
nextBelieves.push_back(nextBelievesInAction);
// do one step here to get the best action in the initial state
ValueType chosenValue = min ? storm::utility::infinity<ValueType>()
: -storm::utility::infinity<ValueType>();
uint64_t chosenActionIndex = std::numeric_limits<uint64_t>::infinity();
ValueType currentValue;
for (uint64_t action = 0; action < initialNumChoices; ++action) {
currentValue = storm::utility::zero<ValueType>(); // simply change this for rewards?
for (auto iter = observationProbabilities[initialBelief.id][action].begin();
iter != observationProbabilities[initialBelief.id][action].end(); ++iter) {
uint32_t observation = iter->first;
storm::pomdp::Belief<ValueType> nextBelief = beliefList[nextBelieves[initialBelief.id][action][observation]];
// compute subsimplex and lambdas according to the Lovejoy paper to approximate the next belief
temp = computeSubSimplexAndLambdas(
nextBelief.probabilities, gridResolution);
std::vector<std::vector<ValueType>> subSimplex = temp.first; std::vector<std::vector<ValueType>> subSimplex = temp.first;
std::vector<ValueType> lambdas = temp.second; std::vector<ValueType> lambdas = temp.second;
ValueType overApprox = storm::utility::zero<ValueType>();
ValueType sum = storm::utility::zero<ValueType>();
for (size_t j = 0; j < lambdas.size(); ++j) { for (size_t j = 0; j < lambdas.size(); ++j) {
if (lambdas[j] != storm::utility::zero<ValueType>()) { if (lambdas[j] != storm::utility::zero<ValueType>()) {
overApprox += lambdas[j] *
result_backup[getBeliefIdInGrid(beliefGrid, initialBelief.observation,
subSimplex[j])];
sum += lambdas[j] * result.at(
getBeliefIdInVector(beliefGrid, observation, subSimplex[j]));
}
}
currentValue += iter->second * sum;
}
// Update the selected actions
if ((min && cc.isLess(storm::utility::zero<ValueType>(), chosenValue - currentValue)) ||
(!min &&
cc.isLess(storm::utility::zero<ValueType>(), currentValue - chosenValue))) {
chosenValue = currentValue;
chosenActionIndex = action;
} }
} }
chosenActions[initialBelief.id] = chosenActionIndex;*/
std::set<uint64_t> exploredBelieves;
std::deque<uint64_t> believesToBeExplored;
exploredBelieves.insert(initialBelief.id);
believesToBeExplored.push_back(initialBelief.id);
while (!believesToBeExplored.empty()) {
auto currentBeliefId = believesToBeExplored.front();
if (chosenActions.find(currentBeliefId) != chosenActions.end()) {
} else {
}
believesToBeExplored.pop_front();
}
STORM_PRINT("Over-Approximation Result: " << overApprox << std::endl); STORM_PRINT("Over-Approximation Result: " << overApprox << std::endl);
} }
template<typename ValueType, typename RewardModelType> template<typename ValueType, typename RewardModelType>
uint64_t ApproximatePOMDPModelchecker<ValueType, RewardModelType>::getBeliefIdInGrid(
std::vector<Belief<ValueType>> &grid, uint32_t observation, std::vector<ValueType> probabilities) {
uint64_t ApproximatePOMDPModelchecker<ValueType, RewardModelType>::getBeliefIdInVector(
std::vector<storm::pomdp::Belief<ValueType>> &grid, uint32_t observation,
std::vector<ValueType> probabilities) {
for (auto const &belief : grid) { for (auto const &belief : grid) {
if (belief.observation == observation && probabilities.size() == belief.probabilities.size()) {
if (belief.observation == observation) {
if (belief.probabilities == probabilities) { if (belief.probabilities == probabilities) {
STORM_LOG_DEBUG("Found belief with id " << std::to_string(belief.id)); STORM_LOG_DEBUG("Found belief with id " << std::to_string(belief.id));
return belief.id; return belief.id;
@ -189,7 +270,7 @@ namespace storm {
} }
template<typename ValueType, typename RewardModelType> template<typename ValueType, typename RewardModelType>
Belief<ValueType> ApproximatePOMDPModelchecker<ValueType, RewardModelType>::getInitialBelief(
storm::pomdp::Belief<ValueType> ApproximatePOMDPModelchecker<ValueType, RewardModelType>::getInitialBelief(
storm::models::sparse::Pomdp<ValueType, RewardModelType> const &pomdp, uint64_t id) { storm::models::sparse::Pomdp<ValueType, RewardModelType> const &pomdp, uint64_t id) {
STORM_LOG_ASSERT(pomdp.getInitialStates().getNumberOfSetBits() < 2, STORM_LOG_ASSERT(pomdp.getInitialStates().getNumberOfSetBits() < 2,
"POMDP contains more than one initial state"); "POMDP contains more than one initial state");
@ -203,16 +284,18 @@ namespace storm {
observation = pomdp.getObservation(state); observation = pomdp.getObservation(state);
} }
} }
return Belief<ValueType>{id, observation, distribution};
return storm::pomdp::Belief<ValueType>{id, observation, distribution};
} }
template<typename ValueType, typename RewardModelType> template<typename ValueType, typename RewardModelType>
void ApproximatePOMDPModelchecker<ValueType, RewardModelType>::constructBeliefGrid( void ApproximatePOMDPModelchecker<ValueType, RewardModelType>::constructBeliefGrid(
storm::models::sparse::Pomdp<ValueType, RewardModelType> const &pomdp, storm::models::sparse::Pomdp<ValueType, RewardModelType> const &pomdp,
std::set<uint32_t> target_observations, uint64_t gridResolution, std::set<uint32_t> target_observations, uint64_t gridResolution,
std::vector<Belief<ValueType>> &grid, std::vector<bool> &beliefIsKnown) {
std::vector<storm::pomdp::Belief<ValueType>> &beliefList,
std::vector<storm::pomdp::Belief<ValueType>> &grid, std::vector<bool> &beliefIsKnown,
uint64_t nextId) {
bool isTarget; bool isTarget;
uint64_t newId = 0;
uint64_t newId = nextId;
for (uint32_t observation = 0; observation < pomdp.getNrObservations(); ++observation) { for (uint32_t observation = 0; observation < pomdp.getNrObservations(); ++observation) {
std::vector<uint64_t> statesWithObservation = pomdp.getStatesWithObservation(observation); std::vector<uint64_t> statesWithObservation = pomdp.getStatesWithObservation(observation);
@ -224,10 +307,11 @@ namespace storm {
std::vector<ValueType> distribution(pomdp.getNumberOfStates(), std::vector<ValueType> distribution(pomdp.getNumberOfStates(),
storm::utility::zero<ValueType>()); storm::utility::zero<ValueType>());
distribution[statesWithObservation.front()] = storm::utility::one<ValueType>(); distribution[statesWithObservation.front()] = storm::utility::one<ValueType>();
Belief<ValueType> belief = {newId, observation, distribution};
storm::pomdp::Belief<ValueType> belief = {newId, observation, distribution};
STORM_LOG_TRACE( STORM_LOG_TRACE(
"Add Belief " << std::to_string(newId) << " [(" << std::to_string(observation) << ")," "Add Belief " << std::to_string(newId) << " [(" << std::to_string(observation) << "),"
<< distribution << "]"); << distribution << "]");
beliefList.push_back(belief);
grid.push_back(belief); grid.push_back(belief);
beliefIsKnown.push_back(isTarget); beliefIsKnown.push_back(isTarget);
++newId; ++newId;
@ -251,10 +335,11 @@ namespace storm {
helper[statesWithObservation.size() - 1] / helper[statesWithObservation.size() - 1] /
storm::utility::convertNumber<ValueType>(gridResolution); storm::utility::convertNumber<ValueType>(gridResolution);
Belief<ValueType> belief = {newId, observation, distribution};
storm::pomdp::Belief<ValueType> belief = {newId, observation, distribution};
STORM_LOG_TRACE( STORM_LOG_TRACE(
"Add Belief " << std::to_string(newId) << " [(" << std::to_string(observation) "Add Belief " << std::to_string(newId) << " [(" << std::to_string(observation)
<< ")," << distribution << "]"); << ")," << distribution << "]");
beliefList.push_back(belief);
grid.push_back(belief); grid.push_back(belief);
beliefIsKnown.push_back(isTarget); beliefIsKnown.push_back(isTarget);
if (helper[statesWithObservation.size() - 1] == if (helper[statesWithObservation.size() - 1] ==
@ -353,7 +438,8 @@ namespace storm {
template<typename ValueType, typename RewardModelType> template<typename ValueType, typename RewardModelType>
std::map<uint32_t, ValueType> std::map<uint32_t, ValueType>
ApproximatePOMDPModelchecker<ValueType, RewardModelType>::computeObservationProbabilitiesAfterAction( ApproximatePOMDPModelchecker<ValueType, RewardModelType>::computeObservationProbabilitiesAfterAction(
storm::models::sparse::Pomdp<ValueType, RewardModelType> const &pomdp, Belief<ValueType> belief,
storm::models::sparse::Pomdp<ValueType, RewardModelType> const &pomdp,
storm::pomdp::Belief<ValueType> belief,
uint64_t actionIndex) { uint64_t actionIndex) {
std::map<uint32_t, ValueType> res; std::map<uint32_t, ValueType> res;
// the id is not important here as we immediately discard the belief (very hacky, I don't like it either) // the id is not important here as we immediately discard the belief (very hacky, I don't like it either)
@ -373,8 +459,10 @@ namespace storm {
} }
template<typename ValueType, typename RewardModelType> template<typename ValueType, typename RewardModelType>
Belief<ValueType> ApproximatePOMDPModelchecker<ValueType, RewardModelType>::getBeliefAfterAction(
storm::models::sparse::Pomdp<ValueType, RewardModelType> const &pomdp, Belief<ValueType> belief,
storm::pomdp::Belief<ValueType>
ApproximatePOMDPModelchecker<ValueType, RewardModelType>::getBeliefAfterAction(
storm::models::sparse::Pomdp<ValueType, RewardModelType> const &pomdp,
storm::pomdp::Belief<ValueType> belief,
uint64_t actionIndex, uint64_t id) { uint64_t actionIndex, uint64_t id) {
std::vector<ValueType> distributionAfter(pomdp.getNumberOfStates(), storm::utility::zero<ValueType>()); std::vector<ValueType> distributionAfter(pomdp.getNumberOfStates(), storm::utility::zero<ValueType>());
uint32_t observation = 0; uint32_t observation = 0;
@ -388,22 +476,13 @@ namespace storm {
} }
} }
} }
/* Should not be necessary
// We have to normalize the distribution
auto sum = storm::utility::zero<ValueType>();
for(ValueType const& entry : distributionAfter){
sum += entry;
}
for(size_t i = 0; i < pomdp.getNumberOfStates(); ++i){
distributionAfter[i] /= sum;
}*/
return Belief<ValueType>{id, observation, distributionAfter};
return storm::pomdp::Belief<ValueType>{id, observation, distributionAfter};
} }
template<typename ValueType, typename RewardModelType> template<typename ValueType, typename RewardModelType>
Belief<ValueType>
ApproximatePOMDPModelchecker<ValueType, RewardModelType>::getBeliefAfterActionAndObservation(
storm::models::sparse::Pomdp<ValueType, RewardModelType> const &pomdp, Belief<ValueType> belief,
uint64_t ApproximatePOMDPModelchecker<ValueType, RewardModelType>::getBeliefAfterActionAndObservation(
storm::models::sparse::Pomdp<ValueType, RewardModelType> const &pomdp,
std::vector<storm::pomdp::Belief<ValueType>> &beliefList, storm::pomdp::Belief<ValueType> belief,
uint64_t actionIndex, uint32_t observation, uint64_t id) { uint64_t actionIndex, uint32_t observation, uint64_t id) {
std::vector<ValueType> distributionAfter(pomdp.getNumberOfStates(), storm::utility::zero<ValueType>()); std::vector<ValueType> distributionAfter(pomdp.getNumberOfStates(), storm::utility::zero<ValueType>());
for (uint64_t state = 0; state < pomdp.getNumberOfStates(); ++state) { for (uint64_t state = 0; state < pomdp.getNumberOfStates(); ++state) {
@ -425,7 +504,12 @@ namespace storm {
for (size_t i = 0; i < pomdp.getNumberOfStates(); ++i) { for (size_t i = 0; i < pomdp.getNumberOfStates(); ++i) {
distributionAfter[i] /= sum; distributionAfter[i] /= sum;
} }
return Belief<ValueType>{id, observation, distributionAfter};
if (getBeliefIdInVector(beliefList, observation, distributionAfter) != uint64_t(-1)) {
return getBeliefIdInVector(beliefList, observation, distributionAfter);
} else {
beliefList.push_back(storm::pomdp::Belief<ValueType>{id, observation, distributionAfter});
return id;
}
} }

35
src/storm-pomdp/modelchecker/ApproximatePOMDPModelchecker.h
View File

@ -2,21 +2,13 @@
#include "storm/modelchecker/CheckTask.h" #include "storm/modelchecker/CheckTask.h"
#include "storm/models/sparse/Pomdp.h" #include "storm/models/sparse/Pomdp.h"
#include "storm/utility/logging.h" #include "storm/utility/logging.h"
#include "storm-pomdp/storage/Belief.h"
namespace storm { namespace storm {
namespace pomdp { namespace pomdp {
namespace modelchecker { namespace modelchecker {
class POMDPCheckResult; class POMDPCheckResult;
// Structure used to represent a belief
template<typename ValueType>
struct Belief {
uint64_t id;
uint32_t observation;
//TODO make this sparse?
std::vector<ValueType> probabilities;
};
template<class ValueType, typename RewardModelType = models::sparse::StandardRewardModel <ValueType>> template<class ValueType, typename RewardModelType = models::sparse::StandardRewardModel <ValueType>>
class ApproximatePOMDPModelchecker { class ApproximatePOMDPModelchecker {
public: public:
@ -38,7 +30,7 @@ namespace storm {
* @param id * @param id
* @return * @return
*/ */
Belief<ValueType>
storm::pomdp::Belief<ValueType>
getInitialBelief(storm::models::sparse::Pomdp<ValueType, RewardModelType> const &pomdp, uint64_t id); getInitialBelief(storm::models::sparse::Pomdp<ValueType, RewardModelType> const &pomdp, uint64_t id);
@ -61,7 +53,9 @@ namespace storm {
*/ */
void constructBeliefGrid(storm::models::sparse::Pomdp<ValueType, RewardModelType> const &pomdp, void constructBeliefGrid(storm::models::sparse::Pomdp<ValueType, RewardModelType> const &pomdp,
std::set<uint32_t> target_observations, uint64_t gridResolution, std::set<uint32_t> target_observations, uint64_t gridResolution,
std::vector<Belief<ValueType>> &grid, std::vector<bool> &beliefIsKnown);
std::vector<storm::pomdp::Belief<ValueType>> &beliefList,
std::vector<storm::pomdp::Belief<ValueType>> &grid,
std::vector<bool> &beliefIsKnown, uint64_t nextId);
/** /**
@ -73,11 +67,13 @@ namespace storm {
* @return * @return
*/ */
std::map<uint32_t, ValueType> computeObservationProbabilitiesAfterAction( std::map<uint32_t, ValueType> computeObservationProbabilitiesAfterAction(
storm::models::sparse::Pomdp<ValueType, RewardModelType> const &pomdp, Belief<ValueType> belief,
storm::models::sparse::Pomdp<ValueType, RewardModelType> const &pomdp,
storm::pomdp::Belief<ValueType> belief,
uint64_t actionIndex); uint64_t actionIndex);
/** /**
* Helper method to get the next belief that results from a belief by performing an action and observing an observation
* Helper method to get the id of the next belief that results from a belief by performing an action and observing an observation.
* If the belief does not exist yet, it is created and added to the list of all beliefs
* *
* @param pomdp the POMDP on which the evaluation should be performed * @param pomdp the POMDP on which the evaluation should be performed
* @param belief the starting belief * @param belief the starting belief
@ -85,9 +81,10 @@ namespace storm {
* @param observation the observation after the action was performed * @param observation the observation after the action was performed
* @return the resulting belief (observation and distribution) * @return the resulting belief (observation and distribution)
*/ */
Belief<ValueType>
uint64_t
getBeliefAfterActionAndObservation(const models::sparse::Pomdp <ValueType, RewardModelType> &pomdp, getBeliefAfterActionAndObservation(const models::sparse::Pomdp <ValueType, RewardModelType> &pomdp,
Belief<ValueType> belief,
std::vector<storm::pomdp::Belief<ValueType>> &beliefList,
storm::pomdp::Belief<ValueType> belief,
uint64_t actionIndex, uint32_t observation, uint64_t id); uint64_t actionIndex, uint32_t observation, uint64_t id);
/** /**
@ -98,18 +95,18 @@ namespace storm {
* @param actionIndex * @param actionIndex
* @return * @return
*/ */
Belief<ValueType>
storm::pomdp::Belief<ValueType>
getBeliefAfterAction(storm::models::sparse::Pomdp<ValueType, RewardModelType> const &pomdp, getBeliefAfterAction(storm::models::sparse::Pomdp<ValueType, RewardModelType> const &pomdp,
Belief<ValueType> belief, uint64_t actionIndex, uint64_t id);
storm::pomdp::Belief<ValueType> belief, uint64_t actionIndex, uint64_t id);
/** /**
* Helper to get the id of a Belief in the grid
* Helper to get the id of a Belief stored in a given vector structure
* *
* @param observation * @param observation
* @param probabilities * @param probabilities
* @return * @return
*/ */
uint64_t getBeliefIdInGrid(std::vector<Belief<ValueType>> &grid, uint32_t observation,
uint64_t getBeliefIdInVector(std::vector<storm::pomdp::Belief<ValueType>> &grid, uint32_t observation,
std::vector<ValueType> probabilities); std::vector<ValueType> probabilities);
}; };

12
src/storm-pomdp/storage/Belief.h
View File

@ -0,0 +1,12 @@
namespace storm {
namespace pomdp {
// Structure used to represent a belief
template<typename ValueType>
struct Belief {
uint64_t id;
uint32_t observation;
//TODO make this sparse?
std::vector<ValueType> probabilities;
};
}
}
Write Preview
Loading…
Cancel
Save