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

DeterministicSchedsLpChecker: Only consider end components with value zero for all objectives.

tempestpy_adaptions
Tim Quatmann 6 years ago
parent
c8dd748943
commit
5467043807
2 changed files with 45 additions and 61 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 90
      src/storm/modelchecker/multiobjective/deterministicScheds/DeterministicSchedsLpChecker.cpp
  2. 16
      src/storm/solver/IterativeMinMaxLinearEquationSolver.cpp

90
src/storm/modelchecker/multiobjective/deterministicScheds/DeterministicSchedsLpChecker.cpp
View File

@ -204,11 +204,21 @@ namespace storm {
template <typename ModelType, typename GeometryValueType>
std::vector<std::vector<storm::expressions::Variable>> DeterministicSchedsLpChecker<ModelType, GeometryValueType>::createEcVariables(std::vector<storm::expressions::Expression> const& choiceVars) {
// Get the choices that do not induce a value (i.e. reward) for all objectives
storm::storage::BitVector choicesWithValueZero(model.getNumberOfChoices(), true);
for (auto const& objHelper : objectiveHelper) {
for (auto const& value : objHelper.getChoiceValueOffsets()) {
STORM_LOG_ASSERT(!storm::utility::isZero(value.second), "Expected non-zero choice-value offset.");
choicesWithValueZero.set(value.first, false);
}
}
storm::storage::MaximalEndComponentDecomposition<ValueType> mecs(model.getTransitionMatrix(), model.getBackwardTransitions(), storm::storage::BitVector(model.getNumberOfStates(), true), choicesWithValueZero);
auto one = lpModel->getConstant(storm::utility::one<ValueType>());
std::vector<std::vector<storm::expressions::Variable>> result(model.getNumberOfStates());
storm::storage::MaximalEndComponentDecomposition<ValueType> mecs(model);
uint64_t ecCounter = 0;
std::vector<std::vector<storm::expressions::Variable>> result(model.getNumberOfStates());
for (auto const& mec : mecs) {
// Create a submatrix for the current mec as well as a mapping to map back to the original states.
storm::storage::BitVector mecStatesAsBitVector(model.getNumberOfStates(), false);
@ -228,64 +238,38 @@ namespace storm {
// Also assert that not every state takes an ec choice.
auto subEcs = getSubEndComponents(mecTransitions);
for (auto const& subEc : subEcs) {
// get the choices of the current EC with some non-zero value (i.e. reward).
// std::cout << "sub ec choices of ec" << ecCounter << ": " << subEc.second << std::endl;
storm::storage::BitVector subEcChoicesWithValueZero = subEc.second;
// Create a variable that is one iff upon entering this subEC no more choice value is collected.
auto ecVar = lpModel->addBoundedIntegerVariable("ec" + std::to_string(ecCounter++), storm::utility::zero<ValueType>(), storm::utility::one<ValueType>());
// assign this variable to every state in the ec
for (auto const& localSubEcStateIndex : subEc.first) {
uint64_t subEcState = toGlobalStateIndexMapping[localSubEcStateIndex];
result[subEcState].push_back(ecVar);
}
// Create the sum over all choice vars that induce zero choice value
std::vector<storm::expressions::Expression> ecChoiceVars;
uint64_t numSubEcStatesWithMultipleChoices = subEc.first.getNumberOfSetBits();
for (auto const& localSubEcChoiceIndex : subEc.second) {
uint64_t subEcChoice = toGlobalChoiceIndexMapping[localSubEcChoiceIndex];
for (auto const& objHelper : objectiveHelper) {
if (objHelper.getChoiceValueOffsets().count(subEcChoice) > 0) {
STORM_LOG_ASSERT(!storm::utility::isZero(objHelper.getChoiceValueOffsets().at(subEcChoice)), "Expected non-zero choice-value offset.");
subEcChoicesWithValueZero.set(localSubEcChoiceIndex, false);
break;
}
if (choiceVars[subEcChoice].isInitialized()) {
ecChoiceVars.push_back(choiceVars[subEcChoice]);
} else {
// If there is no choiceVariable, it means that this corresponds to a state with just one choice.
assert(numSubEcStatesWithMultipleChoices > 0);
--numSubEcStatesWithMultipleChoices;
}
}
// Check whether each state has at least one zero-valued choice
bool zeroValueSubEc = true;
for (auto const& state : subEc.first) {
if (subEcChoicesWithValueZero.getNextSetIndex(mecTransitions.getRowGroupIndices()[state]) >= mecTransitions.getRowGroupIndices()[state + 1]) {
zeroValueSubEc = false;
break;
}
// Assert that the ecVar is one iff the sum over the zero-value-choice variables equals the number of states in this ec
storm::expressions::Expression ecVarBound = one - lpModel->getConstant(storm::utility::convertNumber<ValueType>(numSubEcStatesWithMultipleChoices)).simplify();
if (!ecChoiceVars.empty()) {
ecVarBound = ecVarBound + storm::expressions::sum(ecChoiceVars);
}
if (zeroValueSubEc) {
// Create a variable that is one iff upon entering this subEC no more choice value is collected.
auto ecVar = lpModel->addBoundedIntegerVariable("ec" + std::to_string(ecCounter++), storm::utility::zero<ValueType>(), storm::utility::one<ValueType>());
// assign this variable to every state in the ec
for (auto const& localSubEcStateIndex : subEc.first) {
uint64_t subEcState = toGlobalStateIndexMapping[localSubEcStateIndex];
result[subEcState].push_back(ecVar);
}
// Create the sum over all choice vars that induce zero choice value
std::vector<storm::expressions::Expression> ecChoiceVars;
uint64_t numSubEcStatesWithMultipleChoices = subEc.first.getNumberOfSetBits();
for (auto const& localSubEcChoiceIndex : subEcChoicesWithValueZero) {
uint64_t subEcChoice = toGlobalChoiceIndexMapping[localSubEcChoiceIndex];
if (choiceVars[subEcChoice].isInitialized()) {
ecChoiceVars.push_back(choiceVars[subEcChoice]);
} else {
// If there is no choiceVariable, it means that this corresponds to a state with just one choice.
assert(numSubEcStatesWithMultipleChoices > 0);
--numSubEcStatesWithMultipleChoices;
}
}
// Assert that the ecVar is one iff the sum over the zero-value-choice variables equals the number of states in this ec
storm::expressions::Expression ecVarBound = one - lpModel->getConstant(storm::utility::convertNumber<ValueType>(numSubEcStatesWithMultipleChoices)).simplify();
if (!ecChoiceVars.empty()) {
ecVarBound = ecVarBound + storm::expressions::sum(ecChoiceVars);
}
if (inOutEncoding()) {
lpModel->addConstraint("", ecVar <= ecVarBound);
} else {
lpModel->addConstraint("", ecVar >= ecVarBound);
}
if (inOutEncoding()) {
lpModel->addConstraint("", ecVar <= ecVarBound);
} else {
lpModel->addConstraint("", ecVar >= ecVarBound);
}
}
}
STORM_LOG_TRACE("Found " << ecCounter << " end components.");
return result;
}

16
src/storm/solver/IterativeMinMaxLinearEquationSolver.cpp
View File

@ -241,7 +241,7 @@ namespace storm {
if (!this->hasUniqueSolution()) { // Traditional value iteration has no requirements if the solution is unique.
// Computing a scheduler is only possible if the solution is unique
if (this->isTrackSchedulerSet()) {
requirements.requireNoEndComponents();
requirements.requireUniqueSolution();
} else {
// As we want the smallest (largest) solution for maximizing (minimizing) equation systems, we have to approach the solution from below (above).
if (!direction || direction.get() == OptimizationDirection::Maximize) {
@ -255,7 +255,7 @@ namespace storm {
} else if (method == MinMaxMethod::IntervalIteration) {
// Interval iteration requires a unique solution and lower+upper bounds
if (!this->hasUniqueSolution()) {
requirements.requireNoEndComponents();
requirements.requireUniqueSolution();
}
requirements.requireBounds();
} else if (method == MinMaxMethod::RationalSearch) {
@ -263,22 +263,22 @@ namespace storm {
requirements.requireLowerBounds();
// The solution needs to be unique in case of minimizing or in cases where we want a scheduler.
if (!this->hasUniqueSolution() && (!direction || direction.get() == OptimizationDirection::Minimize || this->isTrackSchedulerSet())) {
requirements.requireNoEndComponents();
requirements.requireUniqueSolution();
}
} else if (method == MinMaxMethod::PolicyIteration) {
if (!this->hasUniqueSolution()) {
// The initial scheduler shall not select an end component
if (!this->hasNoEndComponents()) {
requirements.requireValidInitialScheduler();
}
} else if (method == MinMaxMethod::SoundValueIteration) {
if (!this->hasUniqueSolution()) {
requirements.requireNoEndComponents();
requirements.requireUniqueSolution();
}
requirements.requireBounds(false);
} else if (method == MinMaxMethod::ViToPi) {
// Since we want to use value iteration to extract an initial scheduler, it helps to eliminate all end components first.
// TODO: We might get around this, as the initial value iteration scheduler is only a heuristic.
// Since we want to use value iteration to extract an initial scheduler, the solution has to be unique.
if (!this->hasUniqueSolution()) {
requirements.requireNoEndComponents();
requirements.requireUniqueSolution();
}
} else {
STORM_LOG_THROW(false, storm::exceptions::InvalidEnvironmentException, "Unsupported technique for iterative MinMax linear equation solver.");

Write Preview
Loading…
Cancel
Save