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/*
* File: ExplicitModelAdapter.h
* Author: Christian Dehnert
*
* Created on March 15, 2013, 11:42 AM
*/
#ifndef STORM_ADAPTERS_EXPLICITMODELADAPTER_H
#define STORM_ADAPTERS_EXPLICITMODELADAPTER_H
#include <memory>
#include <unordered_map>
#include <utility>
#include <vector>
#include <queue>
#include <boost/functional/hash.hpp>
#include <boost/container/flat_set.hpp>
#include "src/ir/Program.h"
#include "src/ir/RewardModel.h"
#include "src/ir/StateReward.h"
#include "src/ir/TransitionReward.h"
#include "src/utility/IRUtility.h"
#include "src/models/AbstractModel.h"
#include "src/models/Dtmc.h"
#include "src/models/Ctmc.h"
#include "src/models/Mdp.h"
#include "src/models/Ctmdp.h"
#include "src/models/AtomicPropositionsLabeling.h"
#include "src/storage/SparseMatrix.h"
#include "src/settings/Settings.h"
#include "src/exceptions/WrongFormatException.h"
#include "log4cplus/logger.h"
#include "log4cplus/loggingmacros.h"
extern log4cplus::Logger logger;
using namespace storm::utility::ir;
namespace storm {
namespace adapters {
template<typename ValueType>
class ExplicitModelAdapter {
public:
// A structure holding information about the reachable state space.
struct StateInformation {
StateInformation() : reachableStates(), stateToIndexMap() {
// Intentionally left empty.
}
// A list of reachable states.
std::vector<StateType*> reachableStates;
// A mapping from states to indices in the list of reachable states.
std::unordered_map<StateType*, uint_fast64_t, StateHash, StateCompare> stateToIndexMap;
};
// A structure holding the individual components of a model.
struct ModelComponents {
ModelComponents() : transitionMatrix(), stateLabeling(), stateRewards(), transitionRewardMatrix(), choiceLabeling() {
// Intentionally left empty.
}
// The transition matrix.
storm::storage::SparseMatrix<ValueType> transitionMatrix;
// The state labeling.
storm::models::AtomicPropositionsLabeling stateLabeling;
// The state reward vector.
std::vector<ValueType> stateRewards;
// A matrix storing the reward for particular transitions.
storm::storage::SparseMatrix<ValueType> transitionRewardMatrix;
// A vector that stores a labeling for each choice.
std::vector<boost::container::flat_set<uint_fast64_t>> choiceLabeling;
};
/*!
* Convert the program given at construction time to an abstract model. The type of the model is the one
* specified in the program. The given reward model name selects the rewards that the model will contain.
*
* @param program The program to translate.
* @param constantDefinitionString A string that contains a comma-separated definition of all undefined
* constants in the model.
* @param rewardModelName The name of reward model to be added to the model. This must be either a reward
* model of the program or the empty string. In the latter case, the constructed model will contain no
* rewards.
* @return The explicit model that was given by the probabilistic program.
*/
static std::unique_ptr<storm::models::AbstractModel<ValueType>> translateProgram(storm::ir::Program program, std::string const& constantDefinitionString = "", std::string const& rewardModelName = "") {
// Start by defining the undefined constants in the model.
defineUndefinedConstants(program, constantDefinitionString);
ModelComponents modelComponents = buildModelComponents(program, rewardModelName);
std::unique_ptr<storm::models::AbstractModel<ValueType>> result;
switch (program.getModelType()) {
case storm::ir::Program::DTMC:
result = std::unique_ptr<storm::models::AbstractModel<ValueType>>(new storm::models::Dtmc<ValueType>(std::move(modelComponents.transitionMatrix), std::move(modelComponents.stateLabeling), rewardModelName != "" ? std::move(modelComponents.stateRewards) : boost::optional<std::vector<ValueType>>(), rewardModelName != "" ? std::move(modelComponents.transitionRewardMatrix) : boost::optional<storm::storage::SparseMatrix<ValueType>>(), std::move(modelComponents.choiceLabeling)));
break;
case storm::ir::Program::CTMC:
result = std::unique_ptr<storm::models::AbstractModel<ValueType>>(new storm::models::Ctmc<ValueType>(std::move(modelComponents.transitionMatrix), std::move(modelComponents.stateLabeling), rewardModelName != "" ? std::move(modelComponents.stateRewards) : boost::optional<std::vector<ValueType>>(), rewardModelName != "" ? std::move(modelComponents.transitionRewardMatrix) : boost::optional<storm::storage::SparseMatrix<ValueType>>(), std::move(modelComponents.choiceLabeling)));
break;
case storm::ir::Program::MDP:
result = std::unique_ptr<storm::models::AbstractModel<ValueType>>(new storm::models::Mdp<ValueType>(std::move(modelComponents.transitionMatrix), std::move(modelComponents.stateLabeling), rewardModelName != "" ? std::move(modelComponents.stateRewards) : boost::optional<std::vector<ValueType>>(), rewardModelName != "" ? std::move(modelComponents.transitionRewardMatrix) : boost::optional<storm::storage::SparseMatrix<ValueType>>(), std::move(modelComponents.choiceLabeling)));
break;
case storm::ir::Program::CTMDP:
result = std::unique_ptr<storm::models::AbstractModel<ValueType>>(new storm::models::Ctmdp<ValueType>(std::move(modelComponents.transitionMatrix), std::move(modelComponents.stateLabeling), rewardModelName != "" ? std::move(modelComponents.stateRewards) : boost::optional<std::vector<ValueType>>(), rewardModelName != "" ? std::move(modelComponents.transitionRewardMatrix) : boost::optional<storm::storage::SparseMatrix<ValueType>>(), std::move(modelComponents.choiceLabeling)));
break;
default:
LOG4CPLUS_ERROR(logger, "Error while creating model from probabilistic program: cannot handle this model type.");
throw storm::exceptions::WrongFormatException() << "Error while creating model from probabilistic program: cannot handle this model type.";
break;
}
// Undefine the constants so that the program can be used again somewhere else.
undefineUndefinedConstants(program);
return result;
}
private:
/*!
* Transforms a state into a somewhat readable string.
*
* @param state The state to transform into a string.
* @return A string representation of the state.
*/
static std::string toString(StateType const* state) {
std::stringstream ss;
for (unsigned int i = 0; i < state->first.size(); i++) ss << state->first[i] << "\t";
for (unsigned int i = 0; i < state->second.size(); i++) ss << state->second[i] << "\t";
return ss.str();
}
/*!
* Applies an update to the given state and returns the resulting new state object. This methods does not
* modify the given state but returns a new one.
*
* @param variableInformation A structure with information about the variables in the program.
* @params state The state to which to apply the update.
* @params update The update to apply.
* @return The resulting state.
*/
static StateType* applyUpdate(VariableInformation const& variableInformation, StateType const* state, storm::ir::Update const& update) {
return applyUpdate(variableInformation, state, state, update);
}
/*!
* Applies an update to the given state and returns the resulting new state object. The update is evaluated
* over the variable values of the given base state. This methods does not modify the given state but
* returns a new one.
*
* @param variableInformation A structure with information about the variables in the program.
* @param state The state to which to apply the update.
* @param baseState The state used for evaluating the update.
* @param update The update to apply.
* @return The resulting state.
*/
static StateType* applyUpdate(VariableInformation const& variableInformation, StateType const* state, StateType const* baseState, storm::ir::Update const& update) {
StateType* newState = new StateType(*state);
for (auto variableAssignmentPair : update.getBooleanAssignments()) {
setValue(newState, variableInformation.booleanVariableToIndexMap.at(variableAssignmentPair.first), variableAssignmentPair.second.getExpression()->getValueAsBool(baseState));
}
for (auto variableAssignmentPair : update.getIntegerAssignments()) {
int_fast64_t newVariableValue = variableAssignmentPair.second.getExpression()->getValueAsInt(baseState);
bool isLegalValueForVariable = newVariableValue >= variableInformation.lowerBounds.at(variableInformation.integerVariableToIndexMap.at(variableAssignmentPair.first)) && newVariableValue <= variableInformation.upperBounds.at(variableInformation.integerVariableToIndexMap.at(variableAssignmentPair.first));
if (!isLegalValueForVariable) {
throw storm::exceptions::InvalidStateException() << "Invalid value '" << newVariableValue << "' for variable \"" << variableInformation.integerVariables.at(variableInformation.integerVariableToIndexMap.at(variableAssignmentPair.first)).getName() << "\". Please strengthen the guards if necessary or enlarge the domains of the variables.";
}
setValue(newState, variableInformation.integerVariableToIndexMap.at(variableAssignmentPair.first), newVariableValue);
}
return newState;
}
/*!
* Retrieves the state id of the given state. If the state has not been encountered yet, it will be added to
* the lists of all states with a new id. If the state was already known, the object that is pointed to by
* the given state pointer is deleted and the old state id is returned. Note that the pointer should not be
* used after invoking this method.
*
* @param state A pointer to a state for which to retrieve the index. This must not be used after the call.
* @param stateInformation The information about the already explored part of the reachable state space.
* @return A pair indicating whether the state was already discovered before and the state id of the state.
*/
static std::pair<bool, uint_fast64_t> getOrAddStateIndex(StateType* state, StateInformation& stateInformation) {
// Check, if the state was already registered.
auto indexIt = stateInformation.stateToIndexMap.find(state);
if (indexIt == stateInformation.stateToIndexMap.end()) {
// The state has not been seen, yet, so add it to the list of all reachable states.
stateInformation.stateToIndexMap[state] = stateInformation.reachableStates.size();
stateInformation.reachableStates.push_back(state);
return std::make_pair(false, stateInformation.stateToIndexMap[state]);
} else {
// The state was already encountered. Delete the copy of the old state and return its index.
delete state;
return std::make_pair(true, indexIt->second);
}
}
/*!
* Retrieves all commands that are labeled with the given label and enabled in the given state, grouped by
* modules.
*
* This function will iterate over all modules and retrieve all commands that are labeled with the given
* action and active (i.e. enabled) in the current state. The result is a list of lists of commands in which
* the inner lists contain all commands of exactly one module. If a module does not have *any* (including
* disabled) commands, there will not be a list of commands of that module in the result. If, however, the
* module has a command with a relevant label, but no enabled one, nothing is returned to indicate that there
* is no legal transition possible.
*
* @param The program in which to search for active commands.
* @param state The current state.
* @param action The action label to select.
* @return A list of lists of active commands or nothing.
*/
static boost::optional<std::vector<std::list<storm::ir::Command>>> getActiveCommandsByAction(storm::ir::Program const& program, StateType const* state, std::string const& action) {
boost::optional<std::vector<std::list<storm::ir::Command>>> result((std::vector<std::list<storm::ir::Command>>()));
// Iterate over all modules.
for (uint_fast64_t i = 0; i < program.getNumberOfModules(); ++i) {
storm::ir::Module const& module = program.getModule(i);
// If the module has no command labeled with the given action, we can skip this module.
if (!module.hasAction(action)) {
continue;
}
std::set<uint_fast64_t> const& commandIndices = module.getCommandsByAction(action);
// If the module contains the action, but there is no command in the module that is labeled with
// this action, we don't have any feasible command combinations.
if (commandIndices.empty()) {
return boost::optional<std::vector<std::list<storm::ir::Command>>>();
}
std::list<storm::ir::Command> commands;
// Look up commands by their indices and add them if the guard evaluates to true in the given state.
for (uint_fast64_t commandIndex : commandIndices) {
storm::ir::Command const& command = module.getCommand(commandIndex);
if (command.getGuard()->getValueAsBool(state)) {
commands.push_back(command);
}
}
// If there was no enabled command although the module has some command with the required action label,
// we must not return anything.
if (commands.size() == 0) {
return boost::optional<std::vector<std::list<storm::ir::Command>>>();
}
result.get().push_back(std::move(commands));
}
return result;
}
static std::list<Choice<ValueType>> getUnlabeledTransitions(storm::ir::Program const& program, StateInformation& stateInformation, VariableInformation const& variableInformation, uint_fast64_t stateIndex, std::queue<uint_fast64_t>& stateQueue) {
std::list<Choice<ValueType>> result;
StateType const* currentState = stateInformation.reachableStates[stateIndex];
// Iterate over all modules.
for (uint_fast64_t i = 0; i < program.getNumberOfModules(); ++i) {
storm::ir::Module const& module = program.getModule(i);
// Iterate over all commands.
for (uint_fast64_t j = 0; j < module.getNumberOfCommands(); ++j) {
storm::ir::Command const& command = module.getCommand(j);
// Only consider unlabeled commands.
if (command.getActionName() != "") continue;
// Skip the command, if it is not enabled.
if (!command.getGuard()->getValueAsBool(currentState)) continue;
result.push_back(Choice<ValueType>(""));
Choice<ValueType>& choice = result.back();
choice.addChoiceLabel(command.getGlobalIndex());
double probabilitySum = 0;
// Iterate over all updates of the current command.
for (uint_fast64_t k = 0; k < command.getNumberOfUpdates(); ++k) {
storm::ir::Update const& update = command.getUpdate(k);
// Obtain target state index.
std::pair<bool, uint_fast64_t> flagTargetStateIndexPair = getOrAddStateIndex(applyUpdate(variableInformation, currentState, update), stateInformation);
// If the state has not been discovered yet, add it to the queue of states to be explored.
if (!flagTargetStateIndexPair.first) {
stateQueue.push(flagTargetStateIndexPair.second);
}
// Update the choice by adding the probability/target state to it.
double probabilityToAdd = update.getLikelihoodExpression()->getValueAsDouble(currentState);
probabilitySum += probabilityToAdd;
boost::container::flat_set<uint_fast64_t> labels;
labels.insert(update.getGlobalIndex());
addProbabilityToChoice(choice, flagTargetStateIndexPair.second, probabilityToAdd, labels);
}
// Check that the resulting distribution is in fact a distribution.
if (std::abs(1 - probabilitySum) > storm::settings::Settings::getInstance()->getOptionByLongName("precision").getArgument(0).getValueAsDouble()) {
LOG4CPLUS_ERROR(logger, "Sum of update probabilities should be one for command:\n\t" << command.toString());
throw storm::exceptions::WrongFormatException() << "Sum of update probabilities should be one for command:\n\t" << command.toString();
}
}
}
return result;
}
static std::list<Choice<ValueType>> getLabeledTransitions(storm::ir::Program const& program, StateInformation& stateInformation, VariableInformation const& variableInformation, uint_fast64_t stateIndex, std::queue<uint_fast64_t>& stateQueue) {
std::list<Choice<ValueType>> result;
for (std::string const& action : program.getActions()) {
StateType const* currentState = stateInformation.reachableStates[stateIndex];
boost::optional<std::vector<std::list<storm::ir::Command>>> optionalActiveCommandLists = getActiveCommandsByAction(program, currentState, action);
// Only process this action label, if there is at least one feasible solution.
if (optionalActiveCommandLists) {
std::vector<std::list<storm::ir::Command>> const& activeCommandList = optionalActiveCommandLists.get();
std::vector<std::list<storm::ir::Command>::const_iterator> iteratorList(activeCommandList.size());
// Initialize the list of iterators.
for (size_t i = 0; i < activeCommandList.size(); ++i) {
iteratorList[i] = activeCommandList[i].cbegin();
}
// As long as there is one feasible combination of commands, keep on expanding it.
bool done = false;
while (!done) {
std::unordered_map<StateType*, storm::storage::LabeledValues<double>, StateHash, StateCompare>* currentTargetStates = new std::unordered_map<StateType*, storm::storage::LabeledValues<double>, StateHash, StateCompare>();
std::unordered_map<StateType*, storm::storage::LabeledValues<double>, StateHash, StateCompare>* newTargetStates = new std::unordered_map<StateType*, storm::storage::LabeledValues<double>, StateHash, StateCompare>();
(*currentTargetStates)[new StateType(*currentState)] = storm::storage::LabeledValues<double>(1.0);
// FIXME: This does not check whether a global variable is written multiple times. While the
// behaviour for this is undefined anyway, a warning should be issued in that case.
for (uint_fast64_t i = 0; i < iteratorList.size(); ++i) {
storm::ir::Command const& command = *iteratorList[i];
for (uint_fast64_t j = 0; j < command.getNumberOfUpdates(); ++j) {
storm::ir::Update const& update = command.getUpdate(j);
for (auto const& stateProbabilityPair : *currentTargetStates) {
StateType* newTargetState = applyUpdate(variableInformation, stateProbabilityPair.first, currentState, update);
storm::storage::LabeledValues<double> newProbability;
double updateProbability = update.getLikelihoodExpression()->getValueAsDouble(currentState);
for (auto const& valueLabelSetPair : stateProbabilityPair.second) {
// Copy the label set, so we can modify it.
boost::container::flat_set<uint_fast64_t> newLabelSet = valueLabelSetPair.second;
newLabelSet.insert(update.getGlobalIndex());
newProbability.addValue(valueLabelSetPair.first * updateProbability, newLabelSet);
}
auto existingStateProbabilityPair = newTargetStates->find(newTargetState);
if (existingStateProbabilityPair == newTargetStates->end()) {
(*newTargetStates)[newTargetState] = newProbability;
} else {
existingStateProbabilityPair->second += newProbability;
// If the state was already seen in one of the other updates, we need to delete this copy.
delete newTargetState;
}
}
}
// If there is one more command to come, shift the target states one time step back.
if (i < iteratorList.size() - 1) {
for (auto const& stateProbabilityPair : *currentTargetStates) {
delete stateProbabilityPair.first;
}
delete currentTargetStates;
currentTargetStates = newTargetStates;
newTargetStates = new std::unordered_map<StateType*, storm::storage::LabeledValues<double>, StateHash, StateCompare>();
}
}
// At this point, we applied all commands of the current command combination and newTargetStates
// contains all target states and their respective probabilities. That means we are now ready to
// add the choice to the list of transitions.
result.push_back(Choice<ValueType>(action));
// Now create the actual distribution.
Choice<ValueType>& choice = result.back();
// Add the labels of all commands to this choice.
for (uint_fast64_t i = 0; i < iteratorList.size(); ++i) {
choice.addChoiceLabel(iteratorList[i]->getGlobalIndex());
}
double probabilitySum = 0;
for (auto const& stateProbabilityPair : *newTargetStates) {
std::pair<bool, uint_fast64_t> flagTargetStateIndexPair = getOrAddStateIndex(stateProbabilityPair.first, stateInformation);
// If the state has not been discovered yet, add it to the queue of states to be explored.
if (!flagTargetStateIndexPair.first) {
stateQueue.push(flagTargetStateIndexPair.second);
}
for (auto const& probabilityLabelPair : stateProbabilityPair.second) {
addProbabilityToChoice(choice, flagTargetStateIndexPair.second, probabilityLabelPair.first, probabilityLabelPair.second);
probabilitySum += probabilityLabelPair.first;
}
}
// Check that the resulting distribution is in fact a distribution.
if (std::abs(1 - probabilitySum) > storm::settings::Settings::getInstance()->getOptionByLongName("precision").getArgument(0).getValueAsDouble()) {
LOG4CPLUS_ERROR(logger, "Sum of update probabilities do not some to one for some command.");
throw storm::exceptions::WrongFormatException() << "Sum of update probabilities do not some to one for some command.";
}
// Dispose of the temporary maps.
delete currentTargetStates;
delete newTargetStates;
// Now, check whether there is one more command combination to consider.
bool movedIterator = false;
for (int_fast64_t j = iteratorList.size() - 1; j >= 0; --j) {
++iteratorList[j];
if (iteratorList[j] != activeCommandList[j].end()) {
movedIterator = true;
} else {
// Reset the iterator to the beginning of the list.
iteratorList[j] = activeCommandList[j].begin();
}
}
done = !movedIterator;
}
}
}
return result;
}
/*!
* Builds the transition matrix and the transition reward matrix based for the given program.
*
* @param program The program for which to build the matrices.
* @param variableInformation A structure containing information about the variables in the program.
* @param transitionRewards A list of transition rewards that are to be considered in the transition reward
* matrix.
* @param stateInformation A structure containing information about the states of the program.
* @param deterministicModel A flag indicating whether the model is supposed to be deterministic or not.
* @param transitionMatrix A reference to an initialized matrix which is filled with all transitions by this
* function.
* @param transitionRewardMatrix A reference to an initialized matrix which is filled with all transition
* rewards by this function.
* @return A tuple containing a vector with all rows at which the nondeterministic choices of each state begin
* and a vector containing the labels associated with each choice.
*/
static std::vector<boost::container::flat_set<uint_fast64_t>> buildMatrices(storm::ir::Program const& program, VariableInformation const& variableInformation, std::vector<storm::ir::TransitionReward> const& transitionRewards, StateInformation& stateInformation, bool deterministicModel, storm::storage::SparseMatrixBuilder<ValueType>& transitionMatrixBuilder, storm::storage::SparseMatrixBuilder<ValueType>& transitionRewardMatrixBuilder) {
std::vector<boost::container::flat_set<uint_fast64_t>> choiceLabels;
// Initialize a queue and insert the initial state.
std::queue<uint_fast64_t> stateQueue;
StateType* initialState = getInitialState(program, variableInformation);
getOrAddStateIndex(initialState, stateInformation);
stateQueue.push(stateInformation.stateToIndexMap[initialState]);
// Now explore the current state until there is no more reachable state.
uint_fast64_t currentRow = 0;
while (!stateQueue.empty()) {
uint_fast64_t currentState = stateQueue.front();
// Retrieve all choices for the current state.
std::list<Choice<ValueType>> allUnlabeledChoices = getUnlabeledTransitions(program, stateInformation, variableInformation, currentState, stateQueue);
std::list<Choice<ValueType>> allLabeledChoices = getLabeledTransitions(program, stateInformation, variableInformation, currentState, stateQueue);
uint_fast64_t totalNumberOfChoices = allUnlabeledChoices.size() + allLabeledChoices.size();
// If the current state does not have a single choice, we equip it with a self-loop if that was
// requested and issue an error otherwise.
if (totalNumberOfChoices == 0) {
if (storm::settings::Settings::getInstance()->isSet("fixDeadlocks")) {
transitionMatrixBuilder.addNextValue(currentRow, currentState, storm::utility::constantOne<ValueType>());
++currentRow;
} else {
LOG4CPLUS_ERROR(logger, "Error while creating sparse matrix from probabilistic program: found deadlock state. For fixing these, please provide the appropriate option.");
throw storm::exceptions::WrongFormatException() << "Error while creating sparse matrix from probabilistic program: found deadlock state. For fixing these, please provide the appropriate option.";
}
} else {
// Then, based on whether the model is deterministic or not, either add the choices individually
// or compose them to one choice.
if (deterministicModel) {
Choice<ValueType> globalChoice("");
std::map<uint_fast64_t, ValueType> stateToRewardMap;
boost::container::flat_set<uint_fast64_t> allChoiceLabels;
// Combine all the choices and scale them with the total number of choices of the current state.
for (auto const& choice : allUnlabeledChoices) {
globalChoice.addChoiceLabels(choice.getChoiceLabels());
for (auto const& stateProbabilityPair : choice) {
globalChoice.getOrAddEntry(stateProbabilityPair.first) += stateProbabilityPair.second / totalNumberOfChoices;
// Now add all rewards that match this choice.
for (auto const& transitionReward : transitionRewards) {
if (transitionReward.getActionName() == "" && transitionReward.getStatePredicate()->getValueAsBool(stateInformation.reachableStates.at(currentState))) {
stateToRewardMap[stateProbabilityPair.first] += ValueType(transitionReward.getRewardValue()->getValueAsDouble(stateInformation.reachableStates.at(currentState)));
}
}
}
}
for (auto const& choice : allLabeledChoices) {
globalChoice.addChoiceLabels(choice.getChoiceLabels());
for (auto const& stateProbabilityPair : choice) {
globalChoice.getOrAddEntry(stateProbabilityPair.first) += stateProbabilityPair.second / totalNumberOfChoices;
// Now add all rewards that match this choice.
for (auto const& transitionReward : transitionRewards) {
if (transitionReward.getActionName() == choice.getActionLabel() && transitionReward.getStatePredicate()->getValueAsBool(stateInformation.reachableStates.at(currentState))) {
stateToRewardMap[stateProbabilityPair.first] += ValueType(transitionReward.getRewardValue()->getValueAsDouble(stateInformation.reachableStates.at(currentState)));
}
}
}
}
// Now add the resulting distribution as the only choice of the current state.
choiceLabels.push_back(globalChoice.getChoiceLabels());
for (auto const& stateProbabilityPair : globalChoice) {
transitionMatrixBuilder.addNextValue(currentRow, stateProbabilityPair.first, stateProbabilityPair.second);
}
// Add all transition rewards to the matrix and add dummy entry if there is none.
if (stateToRewardMap.size() > 0) {
for (auto const& stateRewardPair : stateToRewardMap) {
transitionRewardMatrixBuilder.addNextValue(currentRow, stateRewardPair.first, stateRewardPair.second);
}
}
++currentRow;
} else {
// If the model is nondeterministic, we add all choices individually.
transitionMatrixBuilder.newRowGroup(currentRow);
transitionRewardMatrixBuilder.newRowGroup(currentRow);
// First, process all unlabeled choices.
for (auto const& choice : allUnlabeledChoices) {
std::map<uint_fast64_t, ValueType> stateToRewardMap;
choiceLabels.emplace_back(std::move(choice.getChoiceLabels()));
for (auto const& stateProbabilityPair : choice) {
transitionMatrixBuilder.addNextValue(currentRow, stateProbabilityPair.first, stateProbabilityPair.second);
// Now add all rewards that match this choice.
for (auto const& transitionReward : transitionRewards) {
if (transitionReward.getActionName() == "" && transitionReward.getStatePredicate()->getValueAsBool(stateInformation.reachableStates.at(currentState))) {
stateToRewardMap[stateProbabilityPair.first] += ValueType(transitionReward.getRewardValue()->getValueAsDouble(stateInformation.reachableStates.at(currentState)));
}
}
}
// Add all transition rewards to the matrix and add dummy entry if there is none.
if (stateToRewardMap.size() > 0) {
for (auto const& stateRewardPair : stateToRewardMap) {
transitionRewardMatrixBuilder.addNextValue(currentRow, stateRewardPair.first, stateRewardPair.second);
}
}
++currentRow;
}
// Then, process all labeled choices.
for (auto const& choice : allLabeledChoices) {
std::map<uint_fast64_t, ValueType> stateToRewardMap;
choiceLabels.emplace_back(std::move(choice.getChoiceLabels()));
for (auto const& stateProbabilityPair : choice) {
transitionMatrixBuilder.addNextValue(currentRow, stateProbabilityPair.first, stateProbabilityPair.second);
// Now add all rewards that match this choice.
for (auto const& transitionReward : transitionRewards) {
if (transitionReward.getActionName() == choice.getActionLabel() && transitionReward.getStatePredicate()->getValueAsBool(stateInformation.reachableStates.at(currentState))) {
stateToRewardMap[stateProbabilityPair.first] += ValueType(transitionReward.getRewardValue()->getValueAsDouble(stateInformation.reachableStates.at(currentState)));
}
}
}
// Add all transition rewards to the matrix and add dummy entry if there is none.
if (stateToRewardMap.size() > 0) {
for (auto const& stateRewardPair : stateToRewardMap) {
transitionRewardMatrixBuilder.addNextValue(currentRow, stateRewardPair.first, stateRewardPair.second);
}
}
++currentRow;
}
}
}
stateQueue.pop();
}
return choiceLabels;
}
/*!
* Explores the state space of the given program and returns the components of the model as a result.
*
* @param program The program whose state space to explore.
* @param rewardModelName The name of the reward model that is to be considered. If empty, no reward model
* is considered.
* @return A structure containing the components of the resulting model.
*/
static ModelComponents buildModelComponents(storm::ir::Program const& program, std::string const& rewardModelName) {
ModelComponents modelComponents;
VariableInformation variableInformation = createVariableInformation(program);
// Create the structure for storing the reachable state space.
StateInformation stateInformation;
// Get the selected reward model or create an empty one if none is selected.
storm::ir::RewardModel const& rewardModel = rewardModelName != "" ? program.getRewardModel(rewardModelName) : storm::ir::RewardModel();
// Determine whether we have to combine different choices to one or whether this model can have more than
// one choice per state.
bool deterministicModel = program.getModelType() == storm::ir::Program::DTMC || program.getModelType() == storm::ir::Program::CTMC;
// Build the transition and reward matrices.
storm::storage::SparseMatrixBuilder<ValueType> transitionMatrixBuilder(0, 0, 0, !deterministicModel, 0);
storm::storage::SparseMatrixBuilder<ValueType> transitionRewardMatrixBuilder(0, 0, 0, !deterministicModel, 0);
modelComponents.choiceLabeling = buildMatrices(program, variableInformation, rewardModel.getTransitionRewards(), stateInformation, deterministicModel, transitionMatrixBuilder, transitionRewardMatrixBuilder);
// Finalize the resulting matrices.
modelComponents.transitionMatrix = transitionMatrixBuilder.build();
modelComponents.transitionRewardMatrix = transitionRewardMatrixBuilder.build(modelComponents.transitionMatrix.getRowCount());
// Now build the state labeling.
modelComponents.stateLabeling = buildStateLabeling(program, variableInformation, stateInformation);
// Finally, construct the state rewards.
modelComponents.stateRewards = buildStateRewards(rewardModel.getStateRewards(), stateInformation);
// After everything has been created, we can delete the states.
for (auto state : stateInformation.reachableStates) {
delete state;
}
return modelComponents;
}
/*!
* Builds the state labeling for the given program.
*
* @param program The program for which to build the state labeling.
* @param variableInformation Information about the variables in the program.
* @param stateInformation Information about the state space of the program.
* @return The state labeling of the given program.
*/
static storm::models::AtomicPropositionsLabeling buildStateLabeling(storm::ir::Program const& program, VariableInformation const& variableInformation, StateInformation const& stateInformation) {
std::map<std::string, std::unique_ptr<storm::ir::expressions::BaseExpression>> const& labels = program.getLabels();
storm::models::AtomicPropositionsLabeling result(stateInformation.reachableStates.size(), labels.size() + 1);
// Initialize labeling.
for (auto const& labelExpressionPair : labels) {
result.addAtomicProposition(labelExpressionPair.first);
}
for (uint_fast64_t index = 0; index < stateInformation.reachableStates.size(); index++) {
for (auto const& labelExpressionPair: labels) {
// Add label to state, if the corresponding expression is true.
if (labelExpressionPair.second->getValueAsBool(stateInformation.reachableStates[index])) {
result.addAtomicPropositionToState(labelExpressionPair.first, index);
}
}
}
// Also label the initial state with the special label "init".
result.addAtomicProposition("init");
StateType* initialState = getInitialState(program, variableInformation);
uint_fast64_t initialIndex = stateInformation.stateToIndexMap.at(initialState);
result.addAtomicPropositionToState("init", initialIndex);
delete initialState;
return result;
}
/*!
* Builds the state rewards for the given state space.
*
* @param rewards A vector of state rewards to consider.
* @param stateInformation Information about the state space.
* @return A vector containing the state rewards for the state space.
*/
static std::vector<ValueType> buildStateRewards(std::vector<storm::ir::StateReward> const& rewards, StateInformation const& stateInformation) {
std::vector<ValueType> result(stateInformation.reachableStates.size());
for (uint_fast64_t index = 0; index < stateInformation.reachableStates.size(); index++) {
result[index] = ValueType(0);
for (auto const& reward : rewards) {
// Add this reward to the state if the state is included in the state reward.
if (reward.getStatePredicate()->getValueAsBool(stateInformation.reachableStates[index])) {
result[index] += ValueType(reward.getRewardValue()->getValueAsDouble(stateInformation.reachableStates[index]));
}
}
}
return result;
}
};
} // namespace adapters
} // namespace storm
#endif /* STORM_ADAPTERS_EXPLICITMODELADAPTER_H */