209 lines
11 KiB

#include "GameViHelper.h"
#include "storm/environment/Environment.h"
#include "storm/environment/solver/SolverEnvironment.h"
#include "storm/environment/solver/GameSolverEnvironment.h"
#include "storm/utility/SignalHandler.h"
#include "storm/utility/vector.h"
namespace storm {
namespace modelchecker {
namespace helper {
namespace internal {
template <typename ValueType>
GameViHelper<ValueType>::GameViHelper(storm::storage::SparseMatrix<ValueType> const& transitionMatrix, storm::storage::BitVector statesOfCoalition) : _transitionMatrix(transitionMatrix), _statesOfCoalition(statesOfCoalition) {
// Intentionally left empty.
}
template <typename ValueType>
void GameViHelper<ValueType>::prepareSolversAndMultipliers(const Environment& env) {
_multiplier = storm::solver::MultiplierFactory<ValueType>().create(env, _transitionMatrix);
_x1IsCurrent = false;
}
template <typename ValueType>
void GameViHelper<ValueType>::performValueIteration(Environment const& env, std::vector<ValueType>& x, std::vector<ValueType> b, storm::solver::OptimizationDirection const dir, std::vector<ValueType>& constrainedChoiceValues) {
prepareSolversAndMultipliers(env);
// Get precision for convergence check.
ValueType precision = storm::utility::convertNumber<ValueType>(env.solver().game().getPrecision());
uint64_t maxIter = env.solver().game().getMaximalNumberOfIterations();
_b = b;
//_x1.assign(_transitionMatrix.getRowGroupCount(), storm::utility::zero<ValueType>());
_x1 = x;
_x2 = _x1;
if (this->isProduceSchedulerSet()) {
if (!this->_producedOptimalChoices.is_initialized()) {
this->_producedOptimalChoices.emplace();
}
this->_producedOptimalChoices->resize(this->_transitionMatrix.getRowGroupCount());
}
uint64_t iter = 0;
constrainedChoiceValues = std::vector<ValueType>(b.size(), storm::utility::zero<ValueType>());
while (iter < maxIter) {
if(iter == maxIter - 1) {
_multiplier->multiply(env, xNew(), &_b, constrainedChoiceValues);
auto rowGroupIndices = this->_transitionMatrix.getRowGroupIndices();
rowGroupIndices.erase(rowGroupIndices.begin());
_multiplier->reduce(env, dir, constrainedChoiceValues, rowGroupIndices, xNew());
break;
}
performIterationStep(env, dir);
if (checkConvergence(precision)) {
_multiplier->multiply(env, xNew(), &_b, constrainedChoiceValues);
break;
}
if (storm::utility::resources::isTerminate()) {
break;
}
++iter;
}
x = xNew();
if (isProduceSchedulerSet()) {
// We will be doing one more iteration step and track scheduler choices this time.
performIterationStep(env, dir, &_producedOptimalChoices.get());
}
}
template <typename ValueType>
void GameViHelper<ValueType>::performIterationStep(Environment const& env, storm::solver::OptimizationDirection const dir, std::vector<uint64_t>* choices) {
if (!_multiplier) {
prepareSolversAndMultipliers(env);
}
_x1IsCurrent = !_x1IsCurrent;
if (choices == nullptr) {
_multiplier->multiplyAndReduce(env, dir, xOld(), &_b, xNew(), nullptr, &_statesOfCoalition);
} else {
_multiplier->multiplyAndReduce(env, dir, xOld(), &_b, xNew(), choices, &_statesOfCoalition);
}
}
template <typename ValueType>
bool GameViHelper<ValueType>::checkConvergence(ValueType threshold) const {
STORM_LOG_ASSERT(_multiplier, "tried to check for convergence without doing an iteration first.");
// Now check whether the currently produced results are precise enough
STORM_LOG_ASSERT(threshold > storm::utility::zero<ValueType>(), "Did not expect a non-positive threshold.");
auto x1It = xOld().begin();
auto x1Ite = xOld().end();
auto x2It = xNew().begin();
ValueType maxDiff = (*x2It - *x1It);
ValueType minDiff = maxDiff;
// The difference between maxDiff and minDiff is zero at this point. Thus, it doesn't make sense to check the threshold now.
for (++x1It, ++x2It; x1It != x1Ite; ++x1It, ++x2It) {
ValueType diff = (*x2It - *x1It);
// Potentially update maxDiff or minDiff
bool skipCheck = false;
if (maxDiff < diff) {
maxDiff = diff;
} else if (minDiff > diff) {
minDiff = diff;
} else {
skipCheck = true;
}
// Check convergence
if (!skipCheck && (maxDiff - minDiff) > threshold) {
return false;
}
}
return true;
}
template <typename ValueType>
void GameViHelper<ValueType>::setProduceScheduler(bool value) {
_produceScheduler = value;
}
template <typename ValueType>
bool GameViHelper<ValueType>::isProduceSchedulerSet() const {
return _produceScheduler;
}
template <typename ValueType>
void GameViHelper<ValueType>::updateTransitionMatrix(storm::storage::SparseMatrix<ValueType> newTransitionMatrix) {
_transitionMatrix = newTransitionMatrix;
}
template <typename ValueType>
void GameViHelper<ValueType>::updateStatesOfCoalition(storm::storage::BitVector newStatesOfCoalition) {
_statesOfCoalition = newStatesOfCoalition;
}
template <typename ValueType>
std::vector<uint64_t> const& GameViHelper<ValueType>::getProducedOptimalChoices() const {
STORM_LOG_ASSERT(this->isProduceSchedulerSet(), "Trying to get the produced optimal choices although no scheduler was requested.");
STORM_LOG_ASSERT(this->_producedOptimalChoices.is_initialized(), "Trying to get the produced optimal choices but none were available. Was there a computation call before?");
return this->_producedOptimalChoices.get();
}
template <typename ValueType>
std::vector<uint64_t>& GameViHelper<ValueType>::getProducedOptimalChoices() {
STORM_LOG_ASSERT(this->isProduceSchedulerSet(), "Trying to get the produced optimal choices although no scheduler was requested.");
STORM_LOG_ASSERT(this->_producedOptimalChoices.is_initialized(), "Trying to get the produced optimal choices but none were available. Was there a computation call before?");
return this->_producedOptimalChoices.get();
}
template <typename ValueType>
storm::storage::Scheduler<ValueType> GameViHelper<ValueType>::extractScheduler() const{
auto const& optimalChoices = getProducedOptimalChoices();
storm::storage::Scheduler<ValueType> scheduler(optimalChoices.size());
for (uint64_t state = 0; state < optimalChoices.size(); ++state) {
scheduler.setChoice(optimalChoices[state], state);
}
return scheduler;
}
template <typename ValueType>
void GameViHelper<ValueType>::getChoiceValues(Environment const& env, std::vector<ValueType> const& x, std::vector<ValueType>& choiceValues) {
_multiplier->multiply(env, x, &_b, choiceValues);
}
template <typename ValueType>
void GameViHelper<ValueType>::fillChoiceValuesVector(std::vector<ValueType>& choiceValues, storm::storage::BitVector psiStates, std::vector<storm::storage::SparseMatrix<double>::index_type> rowGroupIndices) {
std::vector<ValueType> allChoices = std::vector<ValueType>(rowGroupIndices.at(rowGroupIndices.size() - 1), storm::utility::zero<ValueType>());
auto choice_it = choiceValues.begin();
for(uint state = 0; state < rowGroupIndices.size() - 1; state++) {
uint rowGroupSize = rowGroupIndices[state + 1] - rowGroupIndices[state];
if (psiStates.get(state)) {
for(uint choice = 0; choice < rowGroupSize; choice++, choice_it++) {
allChoices.at(rowGroupIndices.at(state) + choice) = *choice_it;
}
}
}
choiceValues = allChoices;
}
template <typename ValueType>
std::vector<ValueType>& GameViHelper<ValueType>::xNew() {
return _x1IsCurrent ? _x1 : _x2;
}
template <typename ValueType>
std::vector<ValueType> const& GameViHelper<ValueType>::xNew() const {
return _x1IsCurrent ? _x1 : _x2;
}
template <typename ValueType>
std::vector<ValueType>& GameViHelper<ValueType>::xOld() {
return _x1IsCurrent ? _x2 : _x1;
}
template <typename ValueType>
std::vector<ValueType> const& GameViHelper<ValueType>::xOld() const {
return _x1IsCurrent ? _x2 : _x1;
}
template class GameViHelper<double>;
#ifdef STORM_HAVE_CARL
template class GameViHelper<storm::RationalNumber>;
#endif
}
}
}
}