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586 lines
36 KiB
586 lines
36 KiB
#include "src/generator/PrismNextStateGenerator.h"
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#include <boost/container/flat_map.hpp>
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#include "src/models/sparse/StateLabeling.h"
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#include "src/storage/expressions/SimpleValuation.h"
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#include "src/solver/SmtSolver.h"
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#include "src/utility/constants.h"
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#include "src/utility/macros.h"
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#include "src/exceptions/InvalidArgumentException.h"
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#include "src/exceptions/WrongFormatException.h"
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namespace storm {
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namespace generator {
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template<typename ValueType, typename StateType>
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PrismNextStateGenerator<ValueType, StateType>::PrismNextStateGenerator(storm::prism::Program const& program, NextStateGeneratorOptions const& options) : PrismNextStateGenerator<ValueType, StateType>(program.substituteConstants(), options, false) {
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// Intentionally left empty.
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}
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template<typename ValueType, typename StateType>
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PrismNextStateGenerator<ValueType, StateType>::PrismNextStateGenerator(storm::prism::Program const& program, NextStateGeneratorOptions const& options, bool flag) : NextStateGenerator<ValueType, StateType>(program.getManager(), options), program(program), rewardModels() {
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STORM_LOG_TRACE("Creating next-state generator for PRISM program: " << program);
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STORM_LOG_THROW(!this->program.specifiesSystemComposition(), storm::exceptions::WrongFormatException, "The explicit next-state generator currently does not support custom system compositions.");
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// Only after checking validity of the program, we initialize the variable information.
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this->checkValid();
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this->variableInformation = VariableInformation(program);
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// Create a proper evalator.
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this->evaluator = std::make_unique<storm::expressions::ExpressionEvaluator<ValueType>>(program.getManager());
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if (this->options.isBuildAllRewardModelsSet()) {
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for (auto const& rewardModel : this->program.getRewardModels()) {
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rewardModels.push_back(rewardModel);
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}
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} else {
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// Extract the reward models from the program based on the names we were given.
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for (auto const& rewardModelName : this->options.getRewardModelNames()) {
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if (this->program.hasRewardModel(rewardModelName)) {
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rewardModels.push_back(this->program.getRewardModel(rewardModelName));
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} else {
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STORM_LOG_THROW(rewardModelName.empty(), storm::exceptions::InvalidArgumentException, "Cannot build unknown reward model '" << rewardModelName << "'.");
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STORM_LOG_THROW(this->program.getNumberOfRewardModels() == 1, storm::exceptions::InvalidArgumentException, "Reference to standard reward model is ambiguous.");
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}
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}
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// If no reward model was yet added, but there was one that was given in the options, we try to build the
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// standard reward model.
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if (rewardModels.empty() && !this->options.getRewardModelNames().empty()) {
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rewardModels.push_back(this->program.getRewardModel(0));
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}
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}
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// Determine whether any reward model has state action rewards.
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for (auto const& rewardModel : rewardModels) {
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hasStateActionRewards |= rewardModel.get().hasStateActionRewards();
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}
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// If there are terminal states we need to handle, we now need to translate all labels to expressions.
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if (this->options.hasTerminalStates()) {
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for (auto const& expressionOrLabelAndBool : this->options.getTerminalStates()) {
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if (expressionOrLabelAndBool.first.isExpression()) {
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this->terminalStates.push_back(std::make_pair(expressionOrLabelAndBool.first.getExpression(), expressionOrLabelAndBool.second));
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} else {
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if (program.hasLabel(expressionOrLabelAndBool.first.getLabel())) {
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this->terminalStates.push_back(std::make_pair(this->program.getLabelExpression(expressionOrLabelAndBool.first.getLabel()), expressionOrLabelAndBool.second));
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} else {
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// If the label is not present in the program and is not a special one, we raise an error.
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STORM_LOG_THROW(expressionOrLabelAndBool.first.getLabel() == "init" || expressionOrLabelAndBool.first.getLabel() == "deadlock", storm::exceptions::InvalidArgumentException, "Terminal states refer to illegal label '" << expressionOrLabelAndBool.first.getLabel() << "'.");
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}
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}
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}
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}
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}
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template<typename ValueType, typename StateType>
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void PrismNextStateGenerator<ValueType, StateType>::checkValid() const {
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// If the program still contains undefined constants and we are not in a parametric setting, assemble an appropriate error message.
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#ifdef STORM_HAVE_CARL
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if (!std::is_same<ValueType, storm::RationalFunction>::value && program.hasUndefinedConstants()) {
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#else
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if (program.hasUndefinedConstants()) {
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#endif
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std::vector<std::reference_wrapper<storm::prism::Constant const>> undefinedConstants = program.getUndefinedConstants();
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std::stringstream stream;
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bool printComma = false;
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for (auto const& constant : undefinedConstants) {
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if (printComma) {
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stream << ", ";
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} else {
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printComma = true;
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}
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stream << constant.get().getName() << " (" << constant.get().getType() << ")";
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}
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stream << ".";
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STORM_LOG_THROW(false, storm::exceptions::InvalidArgumentException, "Program still contains these undefined constants: " + stream.str());
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}
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#ifdef STORM_HAVE_CARL
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else if (std::is_same<ValueType, storm::RationalFunction>::value && !program.undefinedConstantsAreGraphPreserving()) {
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STORM_LOG_THROW(false, storm::exceptions::InvalidArgumentException, "The program contains undefined constants that appear in some places other than update probabilities and reward value expressions, which is not admitted.");
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}
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#endif
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}
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template<typename ValueType, typename StateType>
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ModelType PrismNextStateGenerator<ValueType, StateType>::getModelType() const {
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switch (program.getModelType()) {
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case storm::prism::Program::ModelType::DTMC: return ModelType::DTMC;
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case storm::prism::Program::ModelType::CTMC: return ModelType::CTMC;
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case storm::prism::Program::ModelType::MDP: return ModelType::MDP;
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case storm::prism::Program::ModelType::MA: return ModelType::MA;
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default:
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STORM_LOG_THROW(false, storm::exceptions::WrongFormatException, "Invalid model type.");
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}
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}
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template<typename ValueType, typename StateType>
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bool PrismNextStateGenerator<ValueType, StateType>::isDeterministicModel() const {
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return program.isDeterministicModel();
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}
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template<typename ValueType, typename StateType>
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bool PrismNextStateGenerator<ValueType, StateType>::isDiscreteTimeModel() const {
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return program.isDiscreteTimeModel();
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}
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template<typename ValueType, typename StateType>
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std::vector<StateType> PrismNextStateGenerator<ValueType, StateType>::getInitialStates(StateToIdCallback const& stateToIdCallback) {
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// Prepare an SMT solver to enumerate all initial states.
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storm::utility::solver::SmtSolverFactory factory;
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std::unique_ptr<storm::solver::SmtSolver> solver = factory.create(program.getManager());
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std::vector<storm::expressions::Expression> rangeExpressions = program.getAllRangeExpressions();
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for (auto const& expression : rangeExpressions) {
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solver->add(expression);
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}
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solver->add(program.getInitialStatesExpression());
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// Proceed ss long as the solver can still enumerate initial states.
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std::vector<StateType> initialStateIndices;
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while (solver->check() == storm::solver::SmtSolver::CheckResult::Sat) {
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// Create fresh state.
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CompressedState initialState(this->variableInformation.getTotalBitOffset());
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// Read variable assignment from the solution of the solver. Also, create an expression we can use to
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// prevent the variable assignment from being enumerated again.
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storm::expressions::Expression blockingExpression;
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std::shared_ptr<storm::solver::SmtSolver::ModelReference> model = solver->getModel();
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for (auto const& booleanVariable : this->variableInformation.booleanVariables) {
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bool variableValue = model->getBooleanValue(booleanVariable.variable);
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storm::expressions::Expression localBlockingExpression = variableValue ? !booleanVariable.variable : booleanVariable.variable;
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blockingExpression = blockingExpression.isInitialized() ? blockingExpression || localBlockingExpression : localBlockingExpression;
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initialState.set(booleanVariable.bitOffset, variableValue);
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}
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for (auto const& integerVariable : this->variableInformation.integerVariables) {
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int_fast64_t variableValue = model->getIntegerValue(integerVariable.variable);
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storm::expressions::Expression localBlockingExpression = integerVariable.variable != model->getManager().integer(variableValue);
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blockingExpression = blockingExpression.isInitialized() ? blockingExpression || localBlockingExpression : localBlockingExpression;
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initialState.setFromInt(integerVariable.bitOffset, integerVariable.bitWidth, static_cast<uint_fast64_t>(variableValue - integerVariable.lowerBound));
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}
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// Register initial state and return it.
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StateType id = stateToIdCallback(initialState);
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initialStateIndices.push_back(id);
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// Block the current initial state to search for the next one.
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if (!blockingExpression.isInitialized()) {
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break;
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}
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solver->add(blockingExpression);
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}
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return initialStateIndices;
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}
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template<typename ValueType, typename StateType>
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StateBehavior<ValueType, StateType> PrismNextStateGenerator<ValueType, StateType>::expand(StateToIdCallback const& stateToIdCallback) {
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// Prepare the result, in case we return early.
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StateBehavior<ValueType, StateType> result;
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// First, construct the state rewards, as we may return early if there are no choices later and we already
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// need the state rewards then.
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for (auto const& rewardModel : rewardModels) {
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ValueType stateRewardValue = storm::utility::zero<ValueType>();
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if (rewardModel.get().hasStateRewards()) {
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for (auto const& stateReward : rewardModel.get().getStateRewards()) {
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if (this->evaluator->asBool(stateReward.getStatePredicateExpression())) {
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stateRewardValue += ValueType(this->evaluator->asRational(stateReward.getRewardValueExpression()));
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}
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}
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}
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result.addStateReward(stateRewardValue);
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}
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// If a terminal expression was set and we must not expand this state, return now.
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if (!this->terminalStates.empty()) {
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for (auto const& expressionBool : this->terminalStates) {
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if (this->evaluator->asBool(expressionBool.first) == expressionBool.second) {
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return result;
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}
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}
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}
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// Get all choices for the state.
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result.setExpanded();
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std::vector<Choice<ValueType>> allChoices = getUnlabeledChoices(*this->state, stateToIdCallback);
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std::vector<Choice<ValueType>> allLabeledChoices = getLabeledChoices(*this->state, stateToIdCallback);
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for (auto& choice : allLabeledChoices) {
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allChoices.push_back(std::move(choice));
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}
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std::size_t totalNumberOfChoices = allChoices.size();
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// If there is not a single choice, we return immediately, because the state has no behavior (other than
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// the state reward).
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if (totalNumberOfChoices == 0) {
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return result;
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}
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// If the model is a deterministic model, we need to fuse the choices into one.
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if (this->isDeterministicModel() && totalNumberOfChoices > 1) {
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Choice<ValueType> globalChoice;
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// For CTMCs, we need to keep track of the total exit rate to scale the action rewards later. For DTMCs
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// this is equal to the number of choices, which is why we initialize it like this here.
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ValueType totalExitRate = this->isDiscreteTimeModel() ? static_cast<ValueType>(totalNumberOfChoices) : storm::utility::zero<ValueType>();
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// Iterate over all choices and combine the probabilities/rates into one choice.
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for (auto const& choice : allChoices) {
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for (auto const& stateProbabilityPair : choice) {
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if (this->isDiscreteTimeModel()) {
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globalChoice.addProbability(stateProbabilityPair.first, stateProbabilityPair.second / totalNumberOfChoices);
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} else {
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globalChoice.addProbability(stateProbabilityPair.first, stateProbabilityPair.second);
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}
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}
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if (hasStateActionRewards && !this->isDiscreteTimeModel()) {
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totalExitRate += choice.getTotalMass();
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}
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if (this->options.isBuildChoiceLabelsSet()) {
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globalChoice.addLabels(choice.getLabels());
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}
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}
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// Now construct the state-action reward for all selected reward models.
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for (auto const& rewardModel : rewardModels) {
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ValueType stateActionRewardValue = storm::utility::zero<ValueType>();
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if (rewardModel.get().hasStateActionRewards()) {
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for (auto const& stateActionReward : rewardModel.get().getStateActionRewards()) {
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for (auto const& choice : allChoices) {
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if (stateActionReward.getActionIndex() == choice.getActionIndex() && this->evaluator->asBool(stateActionReward.getStatePredicateExpression())) {
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stateActionRewardValue += ValueType(this->evaluator->asRational(stateActionReward.getRewardValueExpression())) * choice.getTotalMass() / totalExitRate;
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}
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}
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}
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}
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globalChoice.addReward(stateActionRewardValue);
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}
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// Move the newly fused choice in place.
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allChoices.clear();
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allChoices.push_back(std::move(globalChoice));
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}
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// Move all remaining choices in place.
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for (auto& choice : allChoices) {
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result.addChoice(std::move(choice));
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}
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this->postprocess(result);
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return result;
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}
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template<typename ValueType, typename StateType>
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CompressedState PrismNextStateGenerator<ValueType, StateType>::applyUpdate(CompressedState const& state, storm::prism::Update const& update) {
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CompressedState newState(state);
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// NOTE: the following process assumes that the assignments of the update are ordered in such a way that the
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// assignments to boolean variables precede the assignments to all integer variables and that within the
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// types, the assignments to variables are ordered (in ascending order) by the expression variables.
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// This is guaranteed for PRISM models, by sorting the assignments as soon as an update is created.
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auto assignmentIt = update.getAssignments().begin();
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auto assignmentIte = update.getAssignments().end();
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// Iterate over all boolean assignments and carry them out.
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auto boolIt = this->variableInformation.booleanVariables.begin();
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for (; assignmentIt != assignmentIte && assignmentIt->getExpression().hasBooleanType(); ++assignmentIt) {
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while (assignmentIt->getVariable() != boolIt->variable) {
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++boolIt;
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}
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newState.set(boolIt->bitOffset, this->evaluator->asBool(assignmentIt->getExpression()));
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}
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// Iterate over all integer assignments and carry them out.
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auto integerIt = this->variableInformation.integerVariables.begin();
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for (; assignmentIt != assignmentIte && assignmentIt->getExpression().hasIntegerType(); ++assignmentIt) {
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while (assignmentIt->getVariable() != integerIt->variable) {
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++integerIt;
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}
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int_fast64_t assignedValue = this->evaluator->asInt(assignmentIt->getExpression());
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STORM_LOG_THROW(assignedValue <= integerIt->upperBound, storm::exceptions::WrongFormatException, "The update " << update << " leads to an out-of-bounds value (" << assignedValue << ") for the variable '" << assignmentIt->getVariableName() << "'.");
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STORM_LOG_THROW(assignedValue >= integerIt->lowerBound, storm::exceptions::WrongFormatException, "The update " << update << " leads to an out-of-bounds value (" << assignedValue << ") for the variable '" << assignmentIt->getVariableName() << "'.");
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newState.setFromInt(integerIt->bitOffset, integerIt->bitWidth, assignedValue - integerIt->lowerBound);
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STORM_LOG_ASSERT(static_cast<int_fast64_t>(newState.getAsInt(integerIt->bitOffset, integerIt->bitWidth)) + integerIt->lowerBound == assignedValue, "Writing to the bit vector bucket failed (read " << newState.getAsInt(integerIt->bitOffset, integerIt->bitWidth) << " but wrote " << assignedValue << ").");
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}
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// Check that we processed all assignments.
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STORM_LOG_ASSERT(assignmentIt == assignmentIte, "Not all assignments were consumed.");
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return newState;
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}
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template<typename ValueType, typename StateType>
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boost::optional<std::vector<std::vector<std::reference_wrapper<storm::prism::Command const>>>> PrismNextStateGenerator<ValueType, StateType>::getActiveCommandsByActionIndex(uint_fast64_t const& actionIndex) {
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boost::optional<std::vector<std::vector<std::reference_wrapper<storm::prism::Command const>>>> result((std::vector<std::vector<std::reference_wrapper<storm::prism::Command const>>>()));
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// Iterate over all modules.
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for (uint_fast64_t i = 0; i < program.getNumberOfModules(); ++i) {
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storm::prism::Module const& module = program.getModule(i);
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// If the module has no command labeled with the given action, we can skip this module.
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if (!module.hasActionIndex(actionIndex)) {
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continue;
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}
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std::set<uint_fast64_t> const& commandIndices = module.getCommandIndicesByActionIndex(actionIndex);
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// If the module contains the action, but there is no command in the module that is labeled with
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// this action, we don't have any feasible command combinations.
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if (commandIndices.empty()) {
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return boost::optional<std::vector<std::vector<std::reference_wrapper<storm::prism::Command const>>>>();
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}
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std::vector<std::reference_wrapper<storm::prism::Command const>> commands;
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// Look up commands by their indices and add them if the guard evaluates to true in the given state.
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for (uint_fast64_t commandIndex : commandIndices) {
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storm::prism::Command const& command = module.getCommand(commandIndex);
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if (this->evaluator->asBool(command.getGuardExpression())) {
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commands.push_back(command);
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}
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}
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// If there was no enabled command although the module has some command with the required action label,
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// we must not return anything.
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if (commands.size() == 0) {
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return boost::optional<std::vector<std::vector<std::reference_wrapper<storm::prism::Command const>>>>();
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}
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result.get().push_back(std::move(commands));
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}
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return result;
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}
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template<typename ValueType, typename StateType>
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std::vector<Choice<ValueType>> PrismNextStateGenerator<ValueType, StateType>::getUnlabeledChoices(CompressedState const& state, StateToIdCallback stateToIdCallback) {
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std::vector<Choice<ValueType>> result;
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// Iterate over all modules.
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for (uint_fast64_t i = 0; i < program.getNumberOfModules(); ++i) {
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storm::prism::Module const& module = program.getModule(i);
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// Iterate over all commands.
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for (uint_fast64_t j = 0; j < module.getNumberOfCommands(); ++j) {
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storm::prism::Command const& command = module.getCommand(j);
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// Only consider unlabeled commands.
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if (command.isLabeled()) continue;
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// Skip the command, if it is not enabled.
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if (!this->evaluator->asBool(command.getGuardExpression())) {
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continue;
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}
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result.push_back(Choice<ValueType>(command.getActionIndex(), command.isMarkovian()));
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Choice<ValueType>& choice = result.back();
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// Remember the command labels only if we were asked to.
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if (this->options.isBuildChoiceLabelsSet()) {
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choice.addLabel(command.getGlobalIndex());
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}
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// Iterate over all updates of the current command.
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ValueType probabilitySum = storm::utility::zero<ValueType>();
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for (uint_fast64_t k = 0; k < command.getNumberOfUpdates(); ++k) {
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storm::prism::Update const& update = command.getUpdate(k);
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// Obtain target state index and add it to the list of known states. If it has not yet been
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// seen, we also add it to the set of states that have yet to be explored.
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StateType stateIndex = stateToIdCallback(applyUpdate(state, update));
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// Update the choice by adding the probability/target state to it.
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ValueType probability = this->evaluator->asRational(update.getLikelihoodExpression());
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choice.addProbability(stateIndex, probability);
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probabilitySum += probability;
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}
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// Create the state-action reward for the newly created choice.
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for (auto const& rewardModel : rewardModels) {
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ValueType stateActionRewardValue = storm::utility::zero<ValueType>();
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if (rewardModel.get().hasStateActionRewards()) {
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for (auto const& stateActionReward : rewardModel.get().getStateActionRewards()) {
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if (stateActionReward.getActionIndex() == choice.getActionIndex() && this->evaluator->asBool(stateActionReward.getStatePredicateExpression())) {
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stateActionRewardValue += ValueType(this->evaluator->asRational(stateActionReward.getRewardValueExpression()));
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}
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}
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}
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choice.addReward(stateActionRewardValue);
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}
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|
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// Check that the resulting distribution is in fact a distribution.
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STORM_LOG_THROW(!program.isDiscreteTimeModel() || this->comparator.isOne(probabilitySum), storm::exceptions::WrongFormatException, "Probabilities do not sum to one for command '" << command << "' (actually sum to " << probabilitySum << ").");
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|
}
|
|
}
|
|
|
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return result;
|
|
}
|
|
|
|
template<typename ValueType, typename StateType>
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std::vector<Choice<ValueType>> PrismNextStateGenerator<ValueType, StateType>::getLabeledChoices(CompressedState const& state, StateToIdCallback stateToIdCallback) {
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std::vector<Choice<ValueType>> result;
|
|
|
|
for (uint_fast64_t actionIndex : program.getSynchronizingActionIndices()) {
|
|
boost::optional<std::vector<std::vector<std::reference_wrapper<storm::prism::Command const>>>> optionalActiveCommandLists = getActiveCommandsByActionIndex(actionIndex);
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|
|
|
// Only process this action label, if there is at least one feasible solution.
|
|
if (optionalActiveCommandLists) {
|
|
std::vector<std::vector<std::reference_wrapper<storm::prism::Command const>>> const& activeCommandList = optionalActiveCommandLists.get();
|
|
std::vector<std::vector<std::reference_wrapper<storm::prism::Command const>>::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) {
|
|
boost::container::flat_map<CompressedState, ValueType>* currentTargetStates = new boost::container::flat_map<CompressedState, ValueType>();
|
|
boost::container::flat_map<CompressedState, ValueType>* newTargetStates = new boost::container::flat_map<CompressedState, ValueType>();
|
|
|
|
currentTargetStates->emplace(state, storm::utility::one<ValueType>());
|
|
|
|
for (uint_fast64_t i = 0; i < iteratorList.size(); ++i) {
|
|
storm::prism::Command const& command = *iteratorList[i];
|
|
for (uint_fast64_t j = 0; j < command.getNumberOfUpdates(); ++j) {
|
|
storm::prism::Update const& update = command.getUpdate(j);
|
|
|
|
for (auto const& stateProbabilityPair : *currentTargetStates) {
|
|
// Compute the new state under the current update and add it to the set of new target states.
|
|
CompressedState newTargetState = applyUpdate(stateProbabilityPair.first, update);
|
|
|
|
// If the new state was already found as a successor state, update the probability
|
|
// and otherwise insert it.
|
|
auto targetStateIt = newTargetStates->find(newTargetState);
|
|
if (targetStateIt != newTargetStates->end()) {
|
|
targetStateIt->second += stateProbabilityPair.second * this->evaluator->asRational(update.getLikelihoodExpression());
|
|
} else {
|
|
newTargetStates->emplace(newTargetState, stateProbabilityPair.second * this->evaluator->asRational(update.getLikelihoodExpression()));
|
|
}
|
|
}
|
|
}
|
|
|
|
// If there is one more command to come, shift the target states one time step back.
|
|
if (i < iteratorList.size() - 1) {
|
|
delete currentTargetStates;
|
|
currentTargetStates = newTargetStates;
|
|
newTargetStates = new boost::container::flat_map<CompressedState, ValueType>();
|
|
}
|
|
}
|
|
|
|
// 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>(actionIndex));
|
|
|
|
// Now create the actual distribution.
|
|
Choice<ValueType>& choice = result.back();
|
|
|
|
// Remember the command labels only if we were asked to.
|
|
if (this->options.isBuildChoiceLabelsSet()) {
|
|
// Add the labels of all commands to this choice.
|
|
for (uint_fast64_t i = 0; i < iteratorList.size(); ++i) {
|
|
choice.addLabel(iteratorList[i]->get().getGlobalIndex());
|
|
}
|
|
}
|
|
|
|
// Add the probabilities/rates to the newly created choice.
|
|
ValueType probabilitySum = storm::utility::zero<ValueType>();
|
|
for (auto const& stateProbabilityPair : *newTargetStates) {
|
|
StateType actualIndex = stateToIdCallback(stateProbabilityPair.first);
|
|
choice.addProbability(actualIndex, stateProbabilityPair.second);
|
|
probabilitySum += stateProbabilityPair.second;
|
|
}
|
|
|
|
// Check that the resulting distribution is in fact a distribution.
|
|
STORM_LOG_THROW(!program.isDiscreteTimeModel() || !this->comparator.isConstant(probabilitySum) || this->comparator.isOne(probabilitySum), storm::exceptions::WrongFormatException, "Sum of update probabilities do not some to one for some command (actually sum to " << probabilitySum << ").");
|
|
|
|
// Create the state-action reward for the newly created choice.
|
|
for (auto const& rewardModel : rewardModels) {
|
|
ValueType stateActionRewardValue = storm::utility::zero<ValueType>();
|
|
if (rewardModel.get().hasStateActionRewards()) {
|
|
for (auto const& stateActionReward : rewardModel.get().getStateActionRewards()) {
|
|
if (stateActionReward.getActionIndex() == choice.getActionIndex() && this->evaluator->asBool(stateActionReward.getStatePredicateExpression())) {
|
|
stateActionRewardValue += ValueType(this->evaluator->asRational(stateActionReward.getRewardValueExpression()));
|
|
}
|
|
}
|
|
}
|
|
choice.addReward(stateActionRewardValue);
|
|
}
|
|
|
|
// 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; !movedIterator && 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;
|
|
}
|
|
|
|
template<typename ValueType, typename StateType>
|
|
storm::models::sparse::StateLabeling PrismNextStateGenerator<ValueType, StateType>::label(storm::storage::BitVectorHashMap<StateType> const& states, std::vector<StateType> const& initialStateIndices, std::vector<StateType> const& deadlockStateIndices) {
|
|
// Gather a vector of labels and their expressions.
|
|
std::vector<std::pair<std::string, storm::expressions::Expression>> labels;
|
|
if (this->options.isBuildAllLabelsSet()) {
|
|
for (auto const& label : program.getLabels()) {
|
|
labels.push_back(std::make_pair(label.getName(), label.getStatePredicateExpression()));
|
|
}
|
|
} else {
|
|
for (auto const& labelName : this->options.getLabelNames()) {
|
|
if (program.hasLabel(labelName)) {
|
|
labels.push_back(std::make_pair(labelName, program.getLabelExpression(labelName)));
|
|
} else {
|
|
STORM_LOG_THROW(labelName == "init" || labelName == "deadlock", storm::exceptions::InvalidArgumentException, "Cannot build labeling for unknown label '" << labelName << "'.");
|
|
}
|
|
}
|
|
}
|
|
|
|
return NextStateGenerator<ValueType, StateType>::label(states, initialStateIndices, deadlockStateIndices, labels);
|
|
}
|
|
|
|
template<typename ValueType, typename StateType>
|
|
std::size_t PrismNextStateGenerator<ValueType, StateType>::getNumberOfRewardModels() const {
|
|
return rewardModels.size();
|
|
}
|
|
|
|
template<typename ValueType, typename StateType>
|
|
RewardModelInformation PrismNextStateGenerator<ValueType, StateType>::getRewardModelInformation(uint64_t const& index) const {
|
|
storm::prism::RewardModel const& rewardModel = rewardModels[index].get();
|
|
return RewardModelInformation(rewardModel.getName(), rewardModel.hasStateRewards(), rewardModel.hasStateActionRewards(), rewardModel.hasTransitionRewards());
|
|
}
|
|
|
|
template class PrismNextStateGenerator<double>;
|
|
|
|
#ifdef STORM_HAVE_CARL
|
|
template class PrismNextStateGenerator<storm::RationalNumber>;
|
|
template class PrismNextStateGenerator<storm::RationalFunction>;
|
|
#endif
|
|
}
|
|
}
|