@ -72,6 +72,17 @@ namespace storm {
memoryLabels . push_back ( boost : : none ) ;
memoryLabels . push_back ( boost : : none ) ;
}
}
}
}
// Compute a mapping for each objective to the set of dimensions it considers
for ( uint64_t objIndex = 0 ; objIndex < this - > objectives . size ( ) ; + + objIndex ) {
storm : : storage : : BitVector dimensions ( subObjectives . size ( ) , false ) ;
for ( uint64_t subObjIndex = 0 ; subObjIndex < subObjectives . size ( ) ; + + subObjIndex ) {
if ( subObjectives [ subObjIndex ] . second = = objIndex ) {
dimensions . set ( subObjIndex , true ) ;
}
}
objectiveDimensions . push_back ( std : : move ( dimensions ) ) ;
}
}
}
template < typename ValueType >
template < typename ValueType >
@ -140,17 +151,49 @@ namespace storm {
template < typename ValueType >
template < typename ValueType >
typename MultiDimensionalRewardUnfolding < ValueType > : : EpochModel const & MultiDimensionalRewardUnfolding < ValueType > : : getModelForEpoch ( Epoch const & epoch ) {
typename MultiDimensionalRewardUnfolding < ValueType > : : EpochModel const & MultiDimensionalRewardUnfolding < ValueType > : : getModelForEpoch ( Epoch const & epoch ) {
// Get the model for the considered class of epochs
EpochClass classOfEpoch = getClassOfEpoch ( epoch ) ;
EpochClass classOfEpoch = getClassOfEpoch ( epoch ) ;
auto findRes = epochModels . find ( classOfEpoch ) ;
auto findRes = epochModels . find ( classOfEpoch ) ;
std : : shared_ptr < EpochModel > epochModel ;
if ( findRes ! = epochModels . end ( ) ) {
if ( findRes ! = epochModels . end ( ) ) {
return findRes - > second ;
epochModel = findRes - > second ;
} else {
} else {
return epochModels . insert ( std : : make_pair ( classOfEpoch , computeModelForEpoch ( epoch ) ) ) . first - > second ;
epochModel = epochModels . insert ( std : : make_pair ( classOfEpoch , computeModelForEpoch ( epoch ) ) ) . first - > second ;
}
}
// Filter out all objective rewards that we do not receive in this particular epoch
epochModel - > objectiveRewardFilter . resize ( objectives . size ( ) ) ;
for ( uint64_t objIndex = 0 ; objIndex < objectives . size ( ) ; + + objIndex ) {
storm : : storage : : BitVector & filter = epochModel - > objectiveRewardFilter [ objIndex ] ;
filter . resize ( epochModel - > objectiveRewards [ objIndex ] . size ( ) ) ;
if ( objectiveDimensions [ objIndex ] . empty ( ) ) {
filter . clear ( ) ;
filter . complement ( ) ;
} else {
for ( uint64_t state = 0 ; state < epochModel - > rewardTransitions . getRowGroupCount ( ) ; + + state ) {
for ( uint64_t choice = epochModel - > rewardTransitions . getRowGroupIndices ( ) [ state ] ; choice < epochModel - > rewardTransitions . getRowGroupIndices ( ) [ state + 1 ] ; + + choice ) {
for ( auto const & dim : objectiveDimensions [ objIndex ] ) {
auto successorEpoch = epoch [ dim ] - ( epochModel - > epochSteps [ choice ] . is_initialized ( ) ? epochModel - > epochSteps [ choice ] . get ( ) [ dim ] : 0 ) ;
if ( successorEpoch > = 0 ) {
filter . set ( choice , true ) ;
} else if ( epochModel - > relevantStates [ dim ] . get ( state ) ) {
filter . set ( choice , false ) ;
break ;
} else {
filter . set ( choice , true ) ;
}
}
}
}
}
}
return * epochModel ;
}
}
template < typename ValueType >
template < typename ValueType >
typename MultiDimensionalRewardUnfolding < ValueType > : : EpochModel MultiDimensionalRewardUnfolding < ValueType > : : computeModelForEpoch ( Epoch const & epoch ) {
std : : shared_ptr < typename MultiDimensionalRewardUnfolding < ValueType > : : EpochModel > MultiDimensionalRewardUnfolding < ValueType > : : computeModelForEpoch ( Epoch const & epoch ) {
storm : : storage : : MemoryStructure memory = computeMemoryStructureForEpoch ( epoch ) ;
storm : : storage : : MemoryStructure memory = computeMemoryStructureForEpoch ( epoch ) ;
auto modelMemoryProductBuilder = memory . product ( model ) ;
auto modelMemoryProductBuilder = memory . product ( model ) ;
@ -158,12 +201,12 @@ namespace storm {
auto modelMemoryProduct = modelMemoryProductBuilder . build ( ) - > template as < storm : : models : : sparse : : Mdp < ValueType > > ( ) ;
auto modelMemoryProduct = modelMemoryProductBuilder . build ( ) - > template as < storm : : models : : sparse : : Mdp < ValueType > > ( ) ;
storm : : storage : : SparseMatrix < ValueType > const & allTransitions = modelMemoryProduct - > getTransitionMatrix ( ) ;
storm : : storage : : SparseMatrix < ValueType > const & allTransitions = modelMemoryProduct - > getTransitionMatrix ( ) ;
EpochModel result ;
std : : shared_ptr < EpochModel > result = std : : make_shared < EpochModel > ( ) ;
storm : : storage : : BitVector rewardChoices ( allTransitions . getRowCount ( ) , false ) ;
storm : : storage : : BitVector rewardChoices ( allTransitions . getRowCount ( ) , false ) ;
result . epochSteps . resize ( modelMemoryProduct - > getNumberOfChoices ( ) ) ;
result - > epochSteps . resize ( modelMemoryProduct - > getNumberOfChoices ( ) ) ;
for ( uint64_t modelState = 0 ; modelState < model . getNumberOfStates ( ) ; + + modelState ) {
for ( uint64_t modelState = 0 ; modelState < model . getNumberOfStates ( ) ; + + modelState ) {
uint64_t numChoices = all Transitions . getRowGroupSize ( modelState ) ;
uint64_t firstChoice = all Transitions . getRowGroupIndices ( ) [ modelState ] ;
uint64_t numChoices = model . get TransitionMatrix ( ) . getRowGroupSize ( modelState ) ;
uint64_t firstChoice = model . get TransitionMatrix ( ) . getRowGroupIndices ( ) [ modelState ] ;
for ( uint64_t choiceOffset = 0 ; choiceOffset < numChoices ; + + choiceOffset ) {
for ( uint64_t choiceOffset = 0 ; choiceOffset < numChoices ; + + choiceOffset ) {
Epoch step ;
Epoch step ;
bool isZeroStep = true ;
bool isZeroStep = true ;
@ -176,95 +219,29 @@ namespace storm {
uint64_t productState = modelMemoryProductBuilder . getResultState ( modelState , memState ) ;
uint64_t productState = modelMemoryProductBuilder . getResultState ( modelState , memState ) ;
uint64_t productChoice = allTransitions . getRowGroupIndices ( ) [ productState ] + choiceOffset ;
uint64_t productChoice = allTransitions . getRowGroupIndices ( ) [ productState ] + choiceOffset ;
assert ( productChoice < allTransitions . getRowGroupIndices ( ) [ productState + 1 ] ) ;
assert ( productChoice < allTransitions . getRowGroupIndices ( ) [ productState + 1 ] ) ;
result . epochSteps [ productChoice ] = step ;
result - > epochSteps [ productChoice ] = step ;
rewardChoices . set ( productChoice , true ) ;
rewardChoices . set ( productChoice , true ) ;
}
}
}
}
}
}
}
}
result . rewardTransitions = allTransitions . filterEntries ( rewardChoices ) ;
result . intermediateTransitions = allTransitions . filterEntries ( ~ rewardChoices ) ;
result - > rewardTransitions = allTransitions . filterEntries ( rewardChoices ) ;
result - > intermediateTransitions = allTransitions . filterEntries ( ~ rewardChoices ) ;
result . objectiveRewards . reserve ( objectives . size ( ) ) ;
for ( uint64_t objIndex = 0 ; objIndex < objectives . size ( ) ; + + objIndex ) {
auto const & formula = * this - > objectives [ objIndex ] . formula ;
if ( formula . isProbabilityOperatorFormula ( ) ) {
storm : : modelchecker : : SparsePropositionalModelChecker < storm : : models : : sparse : : Mdp < ValueType > > mc ( * modelMemoryProduct ) ;
storm : : storage : : BitVector dimensions ( subObjectives . size ( ) , false ) ;
std : : vector < uint64_t > dimensionIndexMap ;
for ( uint64_t subObjIndex = 0 ; subObjIndex < subObjectives . size ( ) ; + + subObjIndex ) {
if ( subObjectives [ subObjIndex ] . second = = objIndex ) {
dimensions . set ( subObjIndex , true ) ;
dimensionIndexMap . push_back ( subObjIndex ) ;
}
}
std : : shared_ptr < storm : : logic : : Formula const > sinkStatesFormula ;
for ( auto const & dim : dimensions ) {
auto memLabelFormula = std : : make_shared < storm : : logic : : AtomicLabelFormula > ( memoryLabels [ dim ] . get ( ) ) ;
if ( sinkStatesFormula ) {
sinkStatesFormula = std : : make_shared < storm : : logic : : BinaryBooleanStateFormula > ( storm : : logic : : BinaryBooleanStateFormula : : OperatorType : : Or , sinkStatesFormula , memLabelFormula ) ;
} else {
sinkStatesFormula = memLabelFormula ;
}
}
sinkStatesFormula = std : : make_shared < storm : : logic : : UnaryBooleanStateFormula > ( storm : : logic : : UnaryBooleanStateFormula : : OperatorType : : Not , sinkStatesFormula ) ;
std : : vector < ValueType > objRew ( allTransitions . getRowCount ( ) , storm : : utility : : zero < ValueType > ( ) ) ;
storm : : storage : : BitVector relevantObjectives ( dimensions . getNumberOfSetBits ( ) ) ;
while ( ! relevantObjectives . full ( ) ) {
relevantObjectives . increment ( ) ;
std : : shared_ptr < storm : : logic : : Formula const > relevantStatesFormula ;
std : : shared_ptr < storm : : logic : : Formula const > goalStatesFormula = storm : : logic : : CloneVisitor ( ) . clone ( * sinkStatesFormula ) ;
for ( uint64_t subObjIndex = 0 ; objIndex < dimensionIndexMap . size ( ) ; + + objIndex ) {
std : : shared_ptr < storm : : logic : : Formula > memLabelFormula = std : : make_shared < storm : : logic : : AtomicLabelFormula > ( memoryLabels [ dimensionIndexMap [ subObjIndex ] ] . get ( ) ) ;
if ( relevantObjectives . get ( subObjIndex ) ) {
auto rightSubFormula = subObjectives [ dimensionIndexMap [ subObjIndex ] ] . first - > asBoundedUntilFormula ( ) . getRightSubformula ( ) . asSharedPointer ( ) ;
goalStatesFormula = std : : make_shared < storm : : logic : : BinaryBooleanStateFormula > ( storm : : logic : : BinaryBooleanStateFormula : : OperatorType : : And , goalStatesFormula , rightSubFormula ) ;
} else {
memLabelFormula = std : : make_shared < storm : : logic : : UnaryBooleanStateFormula > ( storm : : logic : : UnaryBooleanStateFormula : : OperatorType : : Not , memLabelFormula ) ;
}
if ( relevantStatesFormula ) {
relevantStatesFormula = std : : make_shared < storm : : logic : : BinaryBooleanStateFormula > ( storm : : logic : : BinaryBooleanStateFormula : : OperatorType : : And , relevantStatesFormula , memLabelFormula ) ;
} else {
relevantStatesFormula = memLabelFormula ;
}
}
storm : : storage : : BitVector relevantStates = mc . check ( * relevantStatesFormula ) - > asExplicitQualitativeCheckResult ( ) . getTruthValuesVector ( ) ;
storm : : storage : : BitVector goalStates = mc . check ( * goalStatesFormula ) - > asExplicitQualitativeCheckResult ( ) . getTruthValuesVector ( ) ;
storm : : utility : : vector : : addVectors ( objRew , allTransitions . getConstrainedRowGroupSumVector ( relevantStates , goalStates ) , objRew ) ;
}
result . objectiveRewards . push_back ( std : : move ( objRew ) ) ;
// TODO
// Check if the formula is already satisfied in the initial state
// STORM_LOG_THROW((data.originalModel.getInitialStates() & rightSubformulaResult).empty(), storm::exceptions::NotImplementedException, "The Probability for the objective " << *data.objectives.back()->originalFormula << " is always one as the rhs of the until formula is true in the initial state. This (trivial) case is currently not implemented.");
} else if ( formula . isRewardOperatorFormula ( ) ) {
auto const & rewModel = modelMemoryProduct - > getRewardModel ( formula . asRewardOperatorFormula ( ) . getRewardModelName ( ) ) ;
STORM_LOG_THROW ( ! rewModel . hasTransitionRewards ( ) , storm : : exceptions : : NotSupportedException , " Reward model has transition rewards which is not expected. " ) ;
bool rewardCollectedInEpoch = true ;
if ( formula . getSubformula ( ) . isCumulativeRewardFormula ( ) ) {
uint64_t dim = 0 ;
for ( ; subObjectives [ dim ] . second ! = objIndex ; + + dim ) ;
rewardCollectedInEpoch = epoch [ dim ] > = 0 ;
} else {
STORM_LOG_THROW ( formula . getSubformula ( ) . isTotalRewardFormula ( ) , storm : : exceptions : : UnexpectedException , " Unexpected type of formula " < < formula ) ;
}
if ( rewardCollectedInEpoch ) {
result . objectiveRewards . push_back ( rewModel . getTotalRewardVector ( modelMemoryProduct - > getTransitionMatrix ( ) ) ) ;
} else {
result . objectiveRewards . emplace_back ( allTransitions . getRowCount ( ) , storm : : utility : : zero < ValueType > ( ) ) ;
}
result - > objectiveRewards = computeObjectiveRewardsForEpoch ( epoch , modelMemoryProduct ) ;
storm : : modelchecker : : SparsePropositionalModelChecker < storm : : models : : sparse : : Mdp < ValueType > > mc ( * modelMemoryProduct ) ;
result - > relevantStates . reserve ( subObjectives . size ( ) ) ;
for ( auto const & relevantStatesLabel : memoryLabels ) {
if ( relevantStatesLabel ) {
auto relevantStatesFormula = std : : make_shared < storm : : logic : : AtomicLabelFormula > ( relevantStatesLabel . get ( ) ) ;
result - > relevantStates . push_back ( mc . check ( * relevantStatesFormula ) - > asExplicitQualitativeCheckResult ( ) . getTruthValuesVector ( ) ) ;
} else {
} else {
STORM_LOG_THROW ( false , storm : : exceptions : : UnexpectedException , " Unexpected type of formula " < < formula ) ;
result - > relevantStates . push_back ( storm : : storage : : BitVector ( modelMemoryProduct - > getNumberOfStates ( ) , true ) ) ;
}
}
}
}
return result ;
return result ;
}
}
@ -282,14 +259,7 @@ namespace storm {
storm : : storage : : MemoryStructure objMemory = storm : : storage : : MemoryStructureBuilder < ValueType > : : buildTrivialMemoryStructure ( model ) ;
storm : : storage : : MemoryStructure objMemory = storm : : storage : : MemoryStructureBuilder < ValueType > : : buildTrivialMemoryStructure ( model ) ;
storm : : storage : : BitVector dimensions ( subObjectives . size ( ) , false ) ;
for ( uint64_t subObjIndex = 0 ; subObjIndex < subObjectives . size ( ) ; + + subObjIndex ) {
if ( subObjectives [ subObjIndex ] . second = = objIndex ) {
dimensions . set ( subObjIndex , true ) ;
}
}
for ( auto const & dim : dimensions ) {
for ( auto const & dim : objectiveDimensions [ objIndex ] ) {
auto const & subObj = subObjectives [ dim ] ;
auto const & subObj = subObjectives [ dim ] ;
if ( subObj . first - > isBoundedUntilFormula ( ) ) {
if ( subObj . first - > isBoundedUntilFormula ( ) ) {
// Create a memory structure that stores whether a PsiState has already been reached
// Create a memory structure that stores whether a PsiState has already been reached
@ -316,14 +286,14 @@ namespace storm {
// find the memory state that represents that none of the subobjective is relative anymore
// find the memory state that represents that none of the subobjective is relative anymore
storm : : storage : : BitVector sinkStates ( objMemory . getNumberOfStates ( ) , true ) ;
storm : : storage : : BitVector sinkStates ( objMemory . getNumberOfStates ( ) , true ) ;
for ( auto const & dim : dimensions ) {
for ( auto const & dim : objectiveDimensions [ objIndex ] ) {
sinkStates = sinkStates & ~ objMemory . getStateLabeling ( ) . getStates ( memoryLabels [ dim ] . get ( ) ) ;
sinkStates = sinkStates & ~ objMemory . getStateLabeling ( ) . getStates ( memoryLabels [ dim ] . get ( ) ) ;
}
}
assert ( sinkStates . getNumberOfSetBits ( ) = = 1 ) ;
assert ( sinkStates . getNumberOfSetBits ( ) = = 1 ) ;
// When a constraint of at least one until formula is violated, we need to switch to the sink memory state
// When a constraint of at least one until formula is violated, we need to switch to the sink memory state
storm : : storage : : MemoryStructureBuilder < ValueType > objMemBuilder ( objMemory , model ) ;
storm : : storage : : MemoryStructureBuilder < ValueType > objMemBuilder ( objMemory , model ) ;
for ( auto const & dim : dimensions ) {
for ( auto const & dim : objectiveDimensions [ objIndex ] ) {
auto const & subObj = subObjectives [ dim ] ;
auto const & subObj = subObjectives [ dim ] ;
storm : : storage : : BitVector constraintModelStates =
storm : : storage : : BitVector constraintModelStates =
~ ( mc . check ( subObj . first - > asBoundedUntilFormula ( ) . getLeftSubformula ( ) ) - > asExplicitQualitativeCheckResult ( ) . getTruthValuesVector ( ) |
~ ( mc . check ( subObj . first - > asBoundedUntilFormula ( ) . getLeftSubformula ( ) ) - > asExplicitQualitativeCheckResult ( ) . getTruthValuesVector ( ) |
@ -339,7 +309,88 @@ namespace storm {
return memory ;
return memory ;
}
}
template < typename ValueType >
std : : vector < std : : vector < ValueType > > MultiDimensionalRewardUnfolding < ValueType > : : computeObjectiveRewardsForEpoch ( Epoch const & epoch , std : : shared_ptr < storm : : models : : sparse : : Mdp < ValueType > > const & modelMemoryProduct ) const {
std : : vector < std : : vector < ValueType > > objectiveRewards ;
objectiveRewards . reserve ( objectives . size ( ) ) ;
for ( uint64_t objIndex = 0 ; objIndex < objectives . size ( ) ; + + objIndex ) {
auto const & formula = * this - > objectives [ objIndex ] . formula ;
if ( formula . isProbabilityOperatorFormula ( ) ) {
storm : : modelchecker : : SparsePropositionalModelChecker < storm : : models : : sparse : : Mdp < ValueType > > mc ( * modelMemoryProduct ) ;
std : : vector < uint64_t > dimensionIndexMap ;
for ( auto const & globalDimensionIndex : objectiveDimensions [ objIndex ] ) {
dimensionIndexMap . push_back ( globalDimensionIndex ) ;
}
std : : shared_ptr < storm : : logic : : Formula const > sinkStatesFormula ;
for ( auto const & dim : objectiveDimensions [ objIndex ] ) {
auto memLabelFormula = std : : make_shared < storm : : logic : : AtomicLabelFormula > ( memoryLabels [ dim ] . get ( ) ) ;
if ( sinkStatesFormula ) {
sinkStatesFormula = std : : make_shared < storm : : logic : : BinaryBooleanStateFormula > ( storm : : logic : : BinaryBooleanStateFormula : : OperatorType : : Or , sinkStatesFormula , memLabelFormula ) ;
} else {
sinkStatesFormula = memLabelFormula ;
}
}
sinkStatesFormula = std : : make_shared < storm : : logic : : UnaryBooleanStateFormula > ( storm : : logic : : UnaryBooleanStateFormula : : OperatorType : : Not , sinkStatesFormula ) ;
std : : vector < ValueType > objRew ( modelMemoryProduct - > getTransitionMatrix ( ) . getRowCount ( ) , storm : : utility : : zero < ValueType > ( ) ) ;
storm : : storage : : BitVector relevantObjectives ( objectiveDimensions [ objIndex ] . getNumberOfSetBits ( ) ) ;
while ( ! relevantObjectives . full ( ) ) {
relevantObjectives . increment ( ) ;
std : : shared_ptr < storm : : logic : : Formula const > relevantStatesFormula ;
std : : shared_ptr < storm : : logic : : Formula const > goalStatesFormula = storm : : logic : : CloneVisitor ( ) . clone ( * sinkStatesFormula ) ;
for ( uint64_t subObjIndex = 0 ; subObjIndex < dimensionIndexMap . size ( ) ; + + subObjIndex ) {
std : : shared_ptr < storm : : logic : : Formula > memLabelFormula = std : : make_shared < storm : : logic : : AtomicLabelFormula > ( memoryLabels [ dimensionIndexMap [ subObjIndex ] ] . get ( ) ) ;
if ( relevantObjectives . get ( subObjIndex ) ) {
auto rightSubFormula = subObjectives [ dimensionIndexMap [ subObjIndex ] ] . first - > asBoundedUntilFormula ( ) . getRightSubformula ( ) . asSharedPointer ( ) ;
goalStatesFormula = std : : make_shared < storm : : logic : : BinaryBooleanStateFormula > ( storm : : logic : : BinaryBooleanStateFormula : : OperatorType : : And , goalStatesFormula , rightSubFormula ) ;
} else {
memLabelFormula = std : : make_shared < storm : : logic : : UnaryBooleanStateFormula > ( storm : : logic : : UnaryBooleanStateFormula : : OperatorType : : Not , memLabelFormula ) ;
}
if ( relevantStatesFormula ) {
relevantStatesFormula = std : : make_shared < storm : : logic : : BinaryBooleanStateFormula > ( storm : : logic : : BinaryBooleanStateFormula : : OperatorType : : And , relevantStatesFormula , memLabelFormula ) ;
} else {
relevantStatesFormula = memLabelFormula ;
}
}
storm : : storage : : BitVector relevantStates = mc . check ( * relevantStatesFormula ) - > asExplicitQualitativeCheckResult ( ) . getTruthValuesVector ( ) ;
storm : : storage : : BitVector goalStates = mc . check ( * goalStatesFormula ) - > asExplicitQualitativeCheckResult ( ) . getTruthValuesVector ( ) ;
storm : : utility : : vector : : addVectors ( objRew , modelMemoryProduct - > getTransitionMatrix ( ) . getConstrainedRowGroupSumVector ( relevantStates , goalStates ) , objRew ) ;
}
objectiveRewards . push_back ( std : : move ( objRew ) ) ;
// TODO
// Check if the formula is already satisfied in the initial state
// STORM_LOG_THROW((data.originalModel.getInitialStates() & rightSubformulaResult).empty(), storm::exceptions::NotImplementedException, "The Probability for the objective " << *data.objectives.back()->originalFormula << " is always one as the rhs of the until formula is true in the initial state. This (trivial) case is currently not implemented.");
} else if ( formula . isRewardOperatorFormula ( ) ) {
auto const & rewModel = modelMemoryProduct - > getRewardModel ( formula . asRewardOperatorFormula ( ) . getRewardModelName ( ) ) ;
STORM_LOG_THROW ( ! rewModel . hasTransitionRewards ( ) , storm : : exceptions : : NotSupportedException , " Reward model has transition rewards which is not expected. " ) ;
bool rewardCollectedInEpoch = true ;
if ( formula . getSubformula ( ) . isCumulativeRewardFormula ( ) ) {
assert ( objectiveDimensions [ objIndex ] . getNumberOfSetBits ( ) = = 1 ) ;
rewardCollectedInEpoch = epoch [ * objectiveDimensions [ objIndex ] . begin ( ) ] > = 0 ;
} else {
STORM_LOG_THROW ( formula . getSubformula ( ) . isTotalRewardFormula ( ) , storm : : exceptions : : UnexpectedException , " Unexpected type of formula " < < formula ) ;
}
if ( rewardCollectedInEpoch ) {
objectiveRewards . push_back ( rewModel . getTotalRewardVector ( modelMemoryProduct - > getTransitionMatrix ( ) ) ) ;
} else {
objectiveRewards . emplace_back ( modelMemoryProduct - > getTransitionMatrix ( ) . getRowCount ( ) , storm : : utility : : zero < ValueType > ( ) ) ;
}
} else {
STORM_LOG_THROW ( false , storm : : exceptions : : UnexpectedException , " Unexpected type of formula " < < formula ) ;
}
}
return objectiveRewards ;
}
template < typename ValueType >
template < typename ValueType >
void MultiDimensionalRewardUnfolding < ValueType > : : setEpochSolution ( Epoch const & epoch , EpochSolution const & solution ) {
void MultiDimensionalRewardUnfolding < ValueType > : : setEpochSolution ( Epoch const & epoch , EpochSolution const & solution ) {
epochSolutions . emplace ( epoch , solution ) ;
epochSolutions . emplace ( epoch , solution ) ;