diff --git a/src/storm/modelchecker/csl/HybridCtmcCslModelChecker.cpp b/src/storm/modelchecker/csl/HybridCtmcCslModelChecker.cpp
index 6e41f2782..b6d65edf0 100644
--- a/src/storm/modelchecker/csl/HybridCtmcCslModelChecker.cpp
+++ b/src/storm/modelchecker/csl/HybridCtmcCslModelChecker.cpp
@@ -10,6 +10,7 @@
 #include "storm/storage/dd/DdManager.h"
 #include "storm/storage/dd/Add.h"
 #include "storm/storage/dd/Bdd.h"
+#include "storm/utility/FilteredRewardModel.h"
 
 #include "storm/logic/FragmentSpecification.h"
 
@@ -31,7 +32,7 @@ namespace storm {
         template<typename CValueType, typename std::enable_if<storm::NumberTraits<CValueType>::SupportsExponential, int>::type>
         bool HybridCtmcCslModelChecker<ModelType>::canHandleImplementation(CheckTask<storm::logic::Formula, CValueType> const& checkTask) const {
             storm::logic::Formula const& formula = checkTask.getFormula();
-            return formula.isInFragment(storm::logic::csrl().setGloballyFormulasAllowed(false).setLongRunAverageRewardFormulasAllowed(true).setLongRunAverageProbabilitiesAllowed(true).setTimeAllowed(true).setTimeOperatorsAllowed(true));
+            return formula.isInFragment(storm::logic::csrl().setGloballyFormulasAllowed(false).setLongRunAverageRewardFormulasAllowed(true).setLongRunAverageProbabilitiesAllowed(true).setTimeAllowed(true).setTimeOperatorsAllowed(true).setRewardAccumulationAllowed(true));
         }
         
         template <typename ModelType>
@@ -66,8 +67,8 @@ namespace storm {
             storm::logic::EventuallyFormula const& eventuallyFormula = checkTask.getFormula();
             std::unique_ptr<CheckResult> subResultPointer = this->check(env, eventuallyFormula.getSubformula());
             SymbolicQualitativeCheckResult<DdType> const& subResult = subResultPointer->asSymbolicQualitativeCheckResult<DdType>();
-
-            return storm::modelchecker::helper::HybridCtmcCslHelper::computeReachabilityRewards<DdType, ValueType>(env, this->getModel(), this->getModel().getTransitionMatrix(), this->getModel().getExitRateVector(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""), subResult.getTruthValuesVector(), checkTask.isQualitativeSet());
+            auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+            return storm::modelchecker::helper::HybridCtmcCslHelper::computeReachabilityRewards<DdType, ValueType>(env, this->getModel(), this->getModel().getTransitionMatrix(), this->getModel().getExitRateVector(), rewardModel.get(), subResult.getTruthValuesVector(), checkTask.isQualitativeSet());
         }
         
         template<typename ModelType>
@@ -117,7 +118,8 @@ namespace storm {
             storm::logic::CumulativeRewardFormula const& rewardPathFormula = checkTask.getFormula();
 
             STORM_LOG_THROW(rewardPathFormula.getTimeBoundReference().isTimeBound(), storm::exceptions::NotImplementedException, "Currently step-bounded and reward-bounded properties on CTMCs are not supported.");
-            return storm::modelchecker::helper::HybridCtmcCslHelper::computeCumulativeRewards<DdType, ValueType>(env, this->getModel(), this->getModel().getTransitionMatrix(), this->getModel().getExitRateVector(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""), rewardPathFormula.getNonStrictBound<double>());
+            auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+            return storm::modelchecker::helper::HybridCtmcCslHelper::computeCumulativeRewards<DdType, ValueType>(env, this->getModel(), this->getModel().getTransitionMatrix(), this->getModel().getExitRateVector(), rewardModel.get(), rewardPathFormula.getNonStrictBound<double>());
         }
         
         template<typename ModelType>
@@ -131,7 +133,8 @@ namespace storm {
         
         template<typename ModelType>
         std::unique_ptr<CheckResult> HybridCtmcCslModelChecker<ModelType>::computeLongRunAverageRewards(Environment const& env, storm::logic::RewardMeasureType rewardMeasureType, CheckTask<storm::logic::LongRunAverageRewardFormula, ValueType> const& checkTask) {
-            return storm::modelchecker::helper::HybridCtmcCslHelper::computeLongRunAverageRewards<DdType, ValueType>(env, this->getModel(), this->getModel().getTransitionMatrix(), this->getModel().getExitRateVector(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""));
+            auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+            return storm::modelchecker::helper::HybridCtmcCslHelper::computeLongRunAverageRewards<DdType, ValueType>(env, this->getModel(), this->getModel().getTransitionMatrix(), this->getModel().getExitRateVector(), rewardModel.get());
         }
         
         // Explicitly instantiate the model checker.
diff --git a/src/storm/modelchecker/csl/SparseCtmcCslModelChecker.cpp b/src/storm/modelchecker/csl/SparseCtmcCslModelChecker.cpp
index cf2aa5bcb..d084a42e4 100644
--- a/src/storm/modelchecker/csl/SparseCtmcCslModelChecker.cpp
+++ b/src/storm/modelchecker/csl/SparseCtmcCslModelChecker.cpp
@@ -9,6 +9,7 @@
 #include "storm/utility/vector.h"
 #include "storm/utility/graph.h"
 #include "storm/utility/solver.h"
+#include "storm/utility/FilteredRewardModel.h"
 
 #include "storm/modelchecker/results/ExplicitQualitativeCheckResult.h"
 #include "storm/modelchecker/results/ExplicitQuantitativeCheckResult.h"
@@ -37,7 +38,7 @@ namespace storm {
         template<typename CValueType, typename std::enable_if<storm::NumberTraits<CValueType>::SupportsExponential, int>::type>
         bool SparseCtmcCslModelChecker<SparseCtmcModelType>::canHandleImplementation(CheckTask<storm::logic::Formula, CValueType> const& checkTask) const {
             storm::logic::Formula const& formula = checkTask.getFormula();
-            return formula.isInFragment(storm::logic::csrl().setGloballyFormulasAllowed(false).setLongRunAverageRewardFormulasAllowed(true).setLongRunAverageProbabilitiesAllowed(true).setTimeAllowed(true).setTotalRewardFormulasAllowed(true));
+            return formula.isInFragment(storm::logic::csrl().setGloballyFormulasAllowed(false).setLongRunAverageRewardFormulasAllowed(true).setLongRunAverageProbabilitiesAllowed(true).setTimeAllowed(true).setTotalRewardFormulasAllowed(true).setRewardAccumulationAllowed(true));
         }
         
         template <typename SparseCtmcModelType>
@@ -103,7 +104,8 @@ namespace storm {
         std::unique_ptr<CheckResult> SparseCtmcCslModelChecker<SparseCtmcModelType>::computeCumulativeRewards(Environment const& env, storm::logic::RewardMeasureType, CheckTask<storm::logic::CumulativeRewardFormula, ValueType> const& checkTask) {
             storm::logic::CumulativeRewardFormula const& rewardPathFormula = checkTask.getFormula();
             STORM_LOG_THROW(rewardPathFormula.getTimeBoundReference().isTimeBound(), storm::exceptions::NotImplementedException, "Currently step-bounded and reward-bounded properties on CTMCs are not supported.");
-            std::vector<ValueType> numericResult = storm::modelchecker::helper::SparseCtmcCslHelper::computeCumulativeRewards(env, storm::solver::SolveGoal<ValueType>(this->getModel(), checkTask), this->getModel().getTransitionMatrix(), this->getModel().getExitRateVector(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""), rewardPathFormula.getNonStrictBound<double>());
+            auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+            std::vector<ValueType> numericResult = storm::modelchecker::helper::SparseCtmcCslHelper::computeCumulativeRewards(env, storm::solver::SolveGoal<ValueType>(this->getModel(), checkTask), this->getModel().getTransitionMatrix(), this->getModel().getExitRateVector(), rewardModel.get(), rewardPathFormula.getNonStrictBound<double>());
             return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(std::move(numericResult)));
         }
                 
@@ -112,14 +114,15 @@ namespace storm {
             storm::logic::EventuallyFormula const& eventuallyFormula = checkTask.getFormula();
             std::unique_ptr<CheckResult> subResultPointer = this->check(env, eventuallyFormula.getSubformula());
             ExplicitQualitativeCheckResult const& subResult = subResultPointer->asExplicitQualitativeCheckResult();
-            
-            std::vector<ValueType> numericResult = storm::modelchecker::helper::SparseCtmcCslHelper::computeReachabilityRewards(env, storm::solver::SolveGoal<ValueType>(this->getModel(), checkTask), this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), this->getModel().getExitRateVector(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""), subResult.getTruthValuesVector(), checkTask.isQualitativeSet());
+            auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+            std::vector<ValueType> numericResult = storm::modelchecker::helper::SparseCtmcCslHelper::computeReachabilityRewards(env, storm::solver::SolveGoal<ValueType>(this->getModel(), checkTask), this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), this->getModel().getExitRateVector(), rewardModel.get(), subResult.getTruthValuesVector(), checkTask.isQualitativeSet());
             return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(std::move(numericResult)));
         }
         
         template<typename SparseCtmcModelType>
         std::unique_ptr<CheckResult> SparseCtmcCslModelChecker<SparseCtmcModelType>::computeTotalRewards(Environment const& env, storm::logic::RewardMeasureType, CheckTask<storm::logic::TotalRewardFormula, ValueType> const& checkTask) {
-            std::vector<ValueType> numericResult = storm::modelchecker::helper::SparseCtmcCslHelper::computeTotalRewards(env, storm::solver::SolveGoal<ValueType>(this->getModel(), checkTask), this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), this->getModel().getExitRateVector(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""), checkTask.isQualitativeSet());
+            auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+            std::vector<ValueType> numericResult = storm::modelchecker::helper::SparseCtmcCslHelper::computeTotalRewards(env, storm::solver::SolveGoal<ValueType>(this->getModel(), checkTask), this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), this->getModel().getExitRateVector(), rewardModel.get(), checkTask.isQualitativeSet());
             return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(std::move(numericResult)));
         }
         
@@ -137,7 +140,8 @@ namespace storm {
         template <typename SparseCtmcModelType>
         std::unique_ptr<CheckResult> SparseCtmcCslModelChecker<SparseCtmcModelType>::computeLongRunAverageRewards(Environment const& env, storm::logic::RewardMeasureType rewardMeasureType, CheckTask<storm::logic::LongRunAverageRewardFormula, ValueType> const& checkTask) {
             storm::storage::SparseMatrix<ValueType> probabilityMatrix = storm::modelchecker::helper::SparseCtmcCslHelper::computeProbabilityMatrix(this->getModel().getTransitionMatrix(), this->getModel().getExitRateVector());
-            std::vector<ValueType> numericResult = storm::modelchecker::helper::SparseCtmcCslHelper::computeLongRunAverageRewards(env, storm::solver::SolveGoal<ValueType>(this->getModel(), checkTask), probabilityMatrix, checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""), &this->getModel().getExitRateVector());
+            auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+            std::vector<ValueType> numericResult = storm::modelchecker::helper::SparseCtmcCslHelper::computeLongRunAverageRewards(env, storm::solver::SolveGoal<ValueType>(this->getModel(), checkTask), probabilityMatrix, rewardModel.get(), &this->getModel().getExitRateVector());
             return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(std::move(numericResult)));
         }
         
diff --git a/src/storm/modelchecker/csl/SparseMarkovAutomatonCslModelChecker.cpp b/src/storm/modelchecker/csl/SparseMarkovAutomatonCslModelChecker.cpp
index 3a21d36db..7da489e01 100644
--- a/src/storm/modelchecker/csl/SparseMarkovAutomatonCslModelChecker.cpp
+++ b/src/storm/modelchecker/csl/SparseMarkovAutomatonCslModelChecker.cpp
@@ -6,6 +6,7 @@
 
 #include "storm/models/sparse/StandardRewardModel.h"
 
+#include "storm/utility/FilteredRewardModel.h"
 #include "storm/utility/macros.h"
 
 #include "storm/settings/SettingsManager.h"
@@ -35,7 +36,7 @@ namespace storm {
         template<typename CValueType, typename std::enable_if<storm::NumberTraits<CValueType>::SupportsExponential, int>::type>
         bool SparseMarkovAutomatonCslModelChecker<SparseMarkovAutomatonModelType>::canHandleImplementation(CheckTask<storm::logic::Formula, CValueType> const& checkTask) const {
             storm::logic::Formula const& formula = checkTask.getFormula();
-            if(formula.isInFragment(storm::logic::csl().setGloballyFormulasAllowed(false).setNextFormulasAllowed(false).setRewardOperatorsAllowed(true).setReachabilityRewardFormulasAllowed(true).setTotalRewardFormulasAllowed(true).setTimeAllowed(true).setLongRunAverageProbabilitiesAllowed(true).setLongRunAverageRewardFormulasAllowed(true))) {
+            if(formula.isInFragment(storm::logic::csl().setGloballyFormulasAllowed(false).setNextFormulasAllowed(false).setRewardOperatorsAllowed(true).setReachabilityRewardFormulasAllowed(true).setTotalRewardFormulasAllowed(true).setTimeAllowed(true).setLongRunAverageProbabilitiesAllowed(true).setLongRunAverageRewardFormulasAllowed(true).setRewardAccumulationAllowed(true))) {
                 return true;
             } else {
                 // Check whether we consider a multi-objective formula
@@ -105,8 +106,9 @@ namespace storm {
             STORM_LOG_THROW(this->getModel().isClosed(), storm::exceptions::InvalidPropertyException, "Unable to compute reachability rewards in non-closed Markov automaton.");
             std::unique_ptr<CheckResult> subResultPointer = this->check(env, eventuallyFormula.getSubformula());
             ExplicitQualitativeCheckResult const& subResult = subResultPointer->asExplicitQualitativeCheckResult();
-
-            std::vector<ValueType> result = storm::modelchecker::helper::SparseMarkovAutomatonCslHelper::computeReachabilityRewards(env, checkTask.getOptimizationDirection(), this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), this->getModel().getExitRates(), this->getModel().getMarkovianStates(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""), subResult.getTruthValuesVector());
+            
+            auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+            std::vector<ValueType> result = storm::modelchecker::helper::SparseMarkovAutomatonCslHelper::computeReachabilityRewards(env, checkTask.getOptimizationDirection(), this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), this->getModel().getExitRates(), this->getModel().getMarkovianStates(), rewardModel.get(), subResult.getTruthValuesVector());
 
             return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(std::move(result)));
         }
@@ -115,7 +117,8 @@ namespace storm {
         std::unique_ptr<CheckResult> SparseMarkovAutomatonCslModelChecker<SparseMarkovAutomatonModelType>::computeTotalRewards(Environment const& env, storm::logic::RewardMeasureType, CheckTask<storm::logic::TotalRewardFormula, ValueType> const& checkTask) {
             STORM_LOG_THROW(checkTask.isOptimizationDirectionSet(), storm::exceptions::InvalidPropertyException, "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model.");
             STORM_LOG_THROW(this->getModel().isClosed(), storm::exceptions::InvalidPropertyException, "Unable to compute reachability rewards in non-closed Markov automaton.");
-            std::vector<ValueType> result = storm::modelchecker::helper::SparseMarkovAutomatonCslHelper::computeTotalRewards(env, checkTask.getOptimizationDirection(), this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), this->getModel().getExitRates(), this->getModel().getMarkovianStates(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""));
+            auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+            std::vector<ValueType> result = storm::modelchecker::helper::SparseMarkovAutomatonCslHelper::computeTotalRewards(env, checkTask.getOptimizationDirection(), this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), this->getModel().getExitRates(), this->getModel().getMarkovianStates(), rewardModel.get());
 
             return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(std::move(result)));
         }
@@ -136,7 +139,8 @@ namespace storm {
         std::unique_ptr<CheckResult> SparseMarkovAutomatonCslModelChecker<SparseMarkovAutomatonModelType>::computeLongRunAverageRewards(Environment const& env, storm::logic::RewardMeasureType rewardMeasureType, CheckTask<storm::logic::LongRunAverageRewardFormula, ValueType> const& checkTask) {
             STORM_LOG_THROW(checkTask.isOptimizationDirectionSet(), storm::exceptions::InvalidPropertyException, "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model.");
             STORM_LOG_THROW(this->getModel().isClosed(), storm::exceptions::InvalidPropertyException, "Unable to compute long run average rewards in non-closed Markov automaton.");
-            std::vector<ValueType> result = storm::modelchecker::helper::SparseMarkovAutomatonCslHelper::computeLongRunAverageRewards<ValueType, RewardModelType>(env, checkTask.getOptimizationDirection(), this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), this->getModel().getExitRates(), this->getModel().getMarkovianStates(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getUniqueRewardModel());
+            auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+            std::vector<ValueType> result = storm::modelchecker::helper::SparseMarkovAutomatonCslHelper::computeLongRunAverageRewards<ValueType, RewardModelType>(env, checkTask.getOptimizationDirection(), this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), this->getModel().getExitRates(), this->getModel().getMarkovianStates(), rewardModel.get());
             return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(std::move(result)));
         }
         
diff --git a/src/storm/modelchecker/prctl/HybridDtmcPrctlModelChecker.cpp b/src/storm/modelchecker/prctl/HybridDtmcPrctlModelChecker.cpp
index 0654a9788..ecd57182f 100644
--- a/src/storm/modelchecker/prctl/HybridDtmcPrctlModelChecker.cpp
+++ b/src/storm/modelchecker/prctl/HybridDtmcPrctlModelChecker.cpp
@@ -8,6 +8,7 @@
 
 #include "storm/utility/macros.h"
 #include "storm/utility/graph.h"
+#include "storm/utility/FilteredRewardModel.h"
 
 #include "storm/models/symbolic/StandardRewardModel.h"
 
@@ -33,7 +34,7 @@ namespace storm {
         template<typename ModelType>
         bool HybridDtmcPrctlModelChecker<ModelType>::canHandle(CheckTask<storm::logic::Formula, ValueType> const& checkTask) const {
             storm::logic::Formula const& formula = checkTask.getFormula();
-            return formula.isInFragment(storm::logic::prctl().setLongRunAverageRewardFormulasAllowed(true).setLongRunAverageProbabilitiesAllowed(true).setTimeOperatorsAllowed(true).setReachbilityTimeFormulasAllowed(true));
+            return formula.isInFragment(storm::logic::prctl().setLongRunAverageRewardFormulasAllowed(true).setLongRunAverageProbabilitiesAllowed(true).setTimeOperatorsAllowed(true).setReachbilityTimeFormulasAllowed(true).setRewardAccumulationAllowed(true));
         }
                 
         template<typename ModelType>
@@ -78,7 +79,8 @@ namespace storm {
         std::unique_ptr<CheckResult> HybridDtmcPrctlModelChecker<ModelType>::computeCumulativeRewards(Environment const& env, storm::logic::RewardMeasureType, CheckTask<storm::logic::CumulativeRewardFormula, ValueType> const& checkTask) {
             storm::logic::CumulativeRewardFormula const& rewardPathFormula = checkTask.getFormula();
             STORM_LOG_THROW(rewardPathFormula.hasIntegerBound(), storm::exceptions::InvalidPropertyException, "Formula needs to have a discrete time bound.");
-            return storm::modelchecker::helper::HybridDtmcPrctlHelper<DdType, ValueType>::computeCumulativeRewards(env, this->getModel(), this->getModel().getTransitionMatrix(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""), rewardPathFormula.getNonStrictBound<uint64_t>());
+            auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+            return storm::modelchecker::helper::HybridDtmcPrctlHelper<DdType, ValueType>::computeCumulativeRewards(env, this->getModel(), this->getModel().getTransitionMatrix(), rewardModel.get(), rewardPathFormula.getNonStrictBound<uint64_t>());
         }
                 
         template<typename ModelType>
@@ -93,7 +95,8 @@ namespace storm {
             storm::logic::EventuallyFormula const& eventuallyFormula = checkTask.getFormula();
             std::unique_ptr<CheckResult> subResultPointer = this->check(env, eventuallyFormula.getSubformula());
             SymbolicQualitativeCheckResult<DdType> const& subResult = subResultPointer->asSymbolicQualitativeCheckResult<DdType>();
-            return storm::modelchecker::helper::HybridDtmcPrctlHelper<DdType, ValueType>::computeReachabilityRewards(env, this->getModel(), this->getModel().getTransitionMatrix(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""), subResult.getTruthValuesVector(), checkTask.isQualitativeSet());
+            auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+            return storm::modelchecker::helper::HybridDtmcPrctlHelper<DdType, ValueType>::computeReachabilityRewards(env, this->getModel(), this->getModel().getTransitionMatrix(), rewardModel.get(), subResult.getTruthValuesVector(), checkTask.isQualitativeSet());
         }
         
         template<typename ModelType>
@@ -117,7 +120,8 @@ namespace storm {
         
         template<typename ModelType>
         std::unique_ptr<CheckResult> HybridDtmcPrctlModelChecker<ModelType>::computeLongRunAverageRewards(Environment const& env, storm::logic::RewardMeasureType rewardMeasureType, CheckTask<storm::logic::LongRunAverageRewardFormula, ValueType> const& checkTask) {
-            return storm::modelchecker::helper::HybridDtmcPrctlHelper<DdType, ValueType>::computeLongRunAverageRewards(env, this->getModel(), this->getModel().getTransitionMatrix(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""));
+            auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+            return storm::modelchecker::helper::HybridDtmcPrctlHelper<DdType, ValueType>::computeLongRunAverageRewards(env, this->getModel(), this->getModel().getTransitionMatrix(), rewardModel.get());
         }
         
         template class HybridDtmcPrctlModelChecker<storm::models::symbolic::Dtmc<storm::dd::DdType::CUDD, double>>;
diff --git a/src/storm/modelchecker/prctl/HybridMdpPrctlModelChecker.cpp b/src/storm/modelchecker/prctl/HybridMdpPrctlModelChecker.cpp
index 9af47c767..270e99c47 100644
--- a/src/storm/modelchecker/prctl/HybridMdpPrctlModelChecker.cpp
+++ b/src/storm/modelchecker/prctl/HybridMdpPrctlModelChecker.cpp
@@ -19,6 +19,7 @@
 #include "storm/modelchecker/multiobjective/multiObjectiveModelChecking.h"
 
 #include "storm/solver/MinMaxLinearEquationSolver.h"
+#include "storm/utility/FilteredRewardModel.h"
 
 #include "storm/settings/modules/GeneralSettings.h"
 
@@ -39,7 +40,7 @@ namespace storm {
         template<typename ModelType>
         bool HybridMdpPrctlModelChecker<ModelType>::canHandle(CheckTask<storm::logic::Formula, ValueType> const& checkTask) const {
             storm::logic::Formula const& formula = checkTask.getFormula();
-            if (formula.isInFragment(storm::logic::prctl().setLongRunAverageRewardFormulasAllowed(false).setTimeOperatorsAllowed(true).setReachbilityTimeFormulasAllowed(true))) {
+            if (formula.isInFragment(storm::logic::prctl().setLongRunAverageRewardFormulasAllowed(false).setTimeOperatorsAllowed(true).setReachbilityTimeFormulasAllowed(true).setRewardAccumulationAllowed(true))) {
                 return true;
             } else {
                 // Check whether we consider a multi-objective formula
@@ -98,7 +99,8 @@ namespace storm {
             storm::logic::CumulativeRewardFormula const& rewardPathFormula = checkTask.getFormula();
             STORM_LOG_THROW(checkTask.isOptimizationDirectionSet(), storm::exceptions::InvalidPropertyException, "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model.");
             STORM_LOG_THROW(rewardPathFormula.hasIntegerBound(), storm::exceptions::InvalidPropertyException, "Formula needs to have a discrete time bound.");
-            return storm::modelchecker::helper::HybridMdpPrctlHelper<DdType, ValueType>::computeCumulativeRewards(env, checkTask.getOptimizationDirection(), this->getModel(), this->getModel().getTransitionMatrix(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""), rewardPathFormula.getNonStrictBound<uint64_t>());
+            auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+            return storm::modelchecker::helper::HybridMdpPrctlHelper<DdType, ValueType>::computeCumulativeRewards(env, checkTask.getOptimizationDirection(), this->getModel(), this->getModel().getTransitionMatrix(), rewardModel.get(), rewardPathFormula.getNonStrictBound<uint64_t>());
         }
                 
         template<typename ModelType>
@@ -115,7 +117,8 @@ namespace storm {
             STORM_LOG_THROW(checkTask.isOptimizationDirectionSet(), storm::exceptions::InvalidPropertyException, "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model.");
             std::unique_ptr<CheckResult> subResultPointer = this->check(env, eventuallyFormula.getSubformula());
             SymbolicQualitativeCheckResult<DdType> const& subResult = subResultPointer->asSymbolicQualitativeCheckResult<DdType>();
-            return storm::modelchecker::helper::HybridMdpPrctlHelper<DdType, ValueType>::computeReachabilityRewards(env, checkTask.getOptimizationDirection(), this->getModel(), this->getModel().getTransitionMatrix(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""), subResult.getTruthValuesVector(), checkTask.isQualitativeSet());
+            auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+            return storm::modelchecker::helper::HybridMdpPrctlHelper<DdType, ValueType>::computeReachabilityRewards(env, checkTask.getOptimizationDirection(), this->getModel(), this->getModel().getTransitionMatrix(), rewardModel.get(), subResult.getTruthValuesVector(), checkTask.isQualitativeSet());
         }
         
         template<typename ModelType>
diff --git a/src/storm/modelchecker/prctl/SparseDtmcPrctlModelChecker.cpp b/src/storm/modelchecker/prctl/SparseDtmcPrctlModelChecker.cpp
index 7c11c31b8..4a1c22ee9 100644
--- a/src/storm/modelchecker/prctl/SparseDtmcPrctlModelChecker.cpp
+++ b/src/storm/modelchecker/prctl/SparseDtmcPrctlModelChecker.cpp
@@ -4,6 +4,7 @@
 #include <memory>
 
 #include "storm/utility/macros.h"
+#include "storm/utility/FilteredRewardModel.h"
 
 #include "storm/modelchecker/results/ExplicitQualitativeCheckResult.h"
 #include "storm/modelchecker/results/ExplicitQuantitativeCheckResult.h"
@@ -33,7 +34,7 @@ namespace storm {
         template<typename SparseDtmcModelType>
         bool SparseDtmcPrctlModelChecker<SparseDtmcModelType>::canHandle(CheckTask<storm::logic::Formula, ValueType> const& checkTask) const {
             storm::logic::Formula const& formula = checkTask.getFormula();
-            if (formula.isInFragment(storm::logic::prctl().setLongRunAverageRewardFormulasAllowed(true).setLongRunAverageProbabilitiesAllowed(true).setConditionalProbabilityFormulasAllowed(true).setConditionalRewardFormulasAllowed(true).setTotalRewardFormulasAllowed(true).setOnlyEventuallyFormuluasInConditionalFormulasAllowed(true).setRewardBoundedUntilFormulasAllowed(true).setRewardBoundedCumulativeRewardFormulasAllowed(true).setMultiDimensionalBoundedUntilFormulasAllowed(true).setMultiDimensionalCumulativeRewardFormulasAllowed(true).setTimeOperatorsAllowed(true).setReachbilityTimeFormulasAllowed(true))) {
+            if (formula.isInFragment(storm::logic::prctl().setLongRunAverageRewardFormulasAllowed(true).setLongRunAverageProbabilitiesAllowed(true).setConditionalProbabilityFormulasAllowed(true).setConditionalRewardFormulasAllowed(true).setTotalRewardFormulasAllowed(true).setOnlyEventuallyFormuluasInConditionalFormulasAllowed(true).setRewardBoundedUntilFormulasAllowed(true).setRewardBoundedCumulativeRewardFormulasAllowed(true).setMultiDimensionalBoundedUntilFormulasAllowed(true).setMultiDimensionalCumulativeRewardFormulasAllowed(true).setTimeOperatorsAllowed(true).setReachbilityTimeFormulasAllowed(true).setRewardAccumulationAllowed(true))) {
                 return true;
             } else if (formula.isInFragment(storm::logic::quantiles())) {
                 if (this->getModel().getInitialStates().getNumberOfSetBits() > 1) return false;
@@ -101,6 +102,7 @@ namespace storm {
             storm::logic::CumulativeRewardFormula const& rewardPathFormula = checkTask.getFormula();
             if (rewardPathFormula.isMultiDimensional() || rewardPathFormula.getTimeBoundReference().isRewardBound()) {
                 STORM_LOG_THROW(checkTask.isOnlyInitialStatesRelevantSet(), storm::exceptions::InvalidOperationException, "Checking non-trivial bounded until probabilities can only be computed for the initial states of the model.");
+                STORM_LOG_THROW(checkTask.getFormula().hasRewardAccumulation(), storm::exceptions::InvalidOperationException, "Checking reward bounded cumulative reward formulas is not supported if reward accumulations are given.");
                 storm::logic::OperatorInformation opInfo;
                 if (checkTask.isBoundSet()) {
                     opInfo.bound = checkTask.getBound();
@@ -110,7 +112,8 @@ namespace storm {
                 return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(std::move(numericResult)));
             } else {
                 STORM_LOG_THROW(rewardPathFormula.hasIntegerBound(), storm::exceptions::InvalidPropertyException, "Formula needs to have a discrete time bound.");
-                std::vector<ValueType> numericResult = storm::modelchecker::helper::SparseDtmcPrctlHelper<ValueType>::computeCumulativeRewards(env, storm::solver::SolveGoal<ValueType>(this->getModel(), checkTask), this->getModel().getTransitionMatrix(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""), rewardPathFormula.getNonStrictBound<uint64_t>());
+                auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+                std::vector<ValueType> numericResult = storm::modelchecker::helper::SparseDtmcPrctlHelper<ValueType>::computeCumulativeRewards(env, storm::solver::SolveGoal<ValueType>(this->getModel(), checkTask), this->getModel().getTransitionMatrix(), rewardModel.get(), rewardPathFormula.getNonStrictBound<uint64_t>());
                 return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(std::move(numericResult)));
             }
         }
@@ -128,7 +131,8 @@ namespace storm {
             storm::logic::EventuallyFormula const& eventuallyFormula = checkTask.getFormula();
             std::unique_ptr<CheckResult> subResultPointer = this->check(env, eventuallyFormula.getSubformula());
             ExplicitQualitativeCheckResult const& subResult = subResultPointer->asExplicitQualitativeCheckResult();
-            std::vector<ValueType> numericResult = storm::modelchecker::helper::SparseDtmcPrctlHelper<ValueType>::computeReachabilityRewards(env, storm::solver::SolveGoal<ValueType>(this->getModel(), checkTask), this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""), subResult.getTruthValuesVector(), checkTask.isQualitativeSet(), checkTask.getHint());
+            auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+            std::vector<ValueType> numericResult = storm::modelchecker::helper::SparseDtmcPrctlHelper<ValueType>::computeReachabilityRewards(env, storm::solver::SolveGoal<ValueType>(this->getModel(), checkTask), this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), rewardModel.get(), subResult.getTruthValuesVector(), checkTask.isQualitativeSet(), checkTask.getHint());
             return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(std::move(numericResult)));
         }
         
@@ -143,7 +147,8 @@ namespace storm {
         
         template<typename SparseDtmcModelType>
         std::unique_ptr<CheckResult> SparseDtmcPrctlModelChecker<SparseDtmcModelType>::computeTotalRewards(Environment const& env, storm::logic::RewardMeasureType, CheckTask<storm::logic::TotalRewardFormula, ValueType> const& checkTask) {
-            std::vector<ValueType> numericResult = storm::modelchecker::helper::SparseDtmcPrctlHelper<ValueType>::computeTotalRewards(env, storm::solver::SolveGoal<ValueType>(this->getModel(), checkTask), this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""), checkTask.isQualitativeSet(), checkTask.getHint());
+            auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+            std::vector<ValueType> numericResult = storm::modelchecker::helper::SparseDtmcPrctlHelper<ValueType>::computeTotalRewards(env, storm::solver::SolveGoal<ValueType>(this->getModel(), checkTask), this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), rewardModel.get(), checkTask.isQualitativeSet(), checkTask.getHint());
             return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(std::move(numericResult)));
         }
 
@@ -158,7 +163,8 @@ namespace storm {
         
         template<typename SparseDtmcModelType>
         std::unique_ptr<CheckResult> SparseDtmcPrctlModelChecker<SparseDtmcModelType>::computeLongRunAverageRewards(Environment const& env, storm::logic::RewardMeasureType rewardMeasureType, CheckTask<storm::logic::LongRunAverageRewardFormula, ValueType> const& checkTask) {
-            std::vector<ValueType> numericResult = storm::modelchecker::helper::SparseCtmcCslHelper::computeLongRunAverageRewards<ValueType>(env, storm::solver::SolveGoal<ValueType>(this->getModel(), checkTask), this->getModel().getTransitionMatrix(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""), nullptr);
+            auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+            std::vector<ValueType> numericResult = storm::modelchecker::helper::SparseCtmcCslHelper::computeLongRunAverageRewards<ValueType>(env, storm::solver::SolveGoal<ValueType>(this->getModel(), checkTask), this->getModel().getTransitionMatrix(), rewardModel.get(), nullptr);
             return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(std::move(numericResult)));
         }
         
diff --git a/src/storm/modelchecker/prctl/SparseMdpPrctlModelChecker.cpp b/src/storm/modelchecker/prctl/SparseMdpPrctlModelChecker.cpp
index bd2dfd326..f12262945 100644
--- a/src/storm/modelchecker/prctl/SparseMdpPrctlModelChecker.cpp
+++ b/src/storm/modelchecker/prctl/SparseMdpPrctlModelChecker.cpp
@@ -4,6 +4,7 @@
 #include "storm/utility/macros.h"
 #include "storm/utility/vector.h"
 #include "storm/utility/graph.h"
+#include "storm/utility/FilteredRewardModel.h"
 
 #include "storm/modelchecker/results/ExplicitQualitativeCheckResult.h"
 #include "storm/modelchecker/results/ExplicitQuantitativeCheckResult.h"
@@ -40,7 +41,7 @@ namespace storm {
         template<typename SparseMdpModelType>
         bool SparseMdpPrctlModelChecker<SparseMdpModelType>::canHandle(CheckTask<storm::logic::Formula, ValueType> const& checkTask) const {
             storm::logic::Formula const& formula = checkTask.getFormula();
-            if (formula.isInFragment(storm::logic::prctl().setLongRunAverageRewardFormulasAllowed(true).setLongRunAverageProbabilitiesAllowed(true).setConditionalProbabilityFormulasAllowed(true).setOnlyEventuallyFormuluasInConditionalFormulasAllowed(true).setTotalRewardFormulasAllowed(true).setRewardBoundedUntilFormulasAllowed(true).setRewardBoundedCumulativeRewardFormulasAllowed(true).setMultiDimensionalBoundedUntilFormulasAllowed(true).setMultiDimensionalCumulativeRewardFormulasAllowed(true).setTimeOperatorsAllowed(true).setReachbilityTimeFormulasAllowed(true))) {
+            if (formula.isInFragment(storm::logic::prctl().setLongRunAverageRewardFormulasAllowed(true).setLongRunAverageProbabilitiesAllowed(true).setConditionalProbabilityFormulasAllowed(true).setOnlyEventuallyFormuluasInConditionalFormulasAllowed(true).setTotalRewardFormulasAllowed(true).setRewardBoundedUntilFormulasAllowed(true).setRewardBoundedCumulativeRewardFormulasAllowed(true).setMultiDimensionalBoundedUntilFormulasAllowed(true).setMultiDimensionalCumulativeRewardFormulasAllowed(true).setTimeOperatorsAllowed(true).setReachbilityTimeFormulasAllowed(true).setRewardAccumulationAllowed(true))) {
                 return true;
             } else if (formula.isInFragment(storm::logic::multiObjective().setCumulativeRewardFormulasAllowed(true).setTimeBoundedCumulativeRewardFormulasAllowed(true).setStepBoundedCumulativeRewardFormulasAllowed(true).setRewardBoundedCumulativeRewardFormulasAllowed(true).setTimeBoundedUntilFormulasAllowed(true).setStepBoundedUntilFormulasAllowed(true).setRewardBoundedUntilFormulasAllowed(true).setMultiDimensionalBoundedUntilFormulasAllowed(true).setMultiDimensionalCumulativeRewardFormulasAllowed(true))) {
                 // Check whether we consider a multi-objective formula
@@ -140,6 +141,7 @@ namespace storm {
             STORM_LOG_THROW(checkTask.isOptimizationDirectionSet(), storm::exceptions::InvalidPropertyException, "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model.");
             if (rewardPathFormula.isMultiDimensional() || rewardPathFormula.getTimeBoundReference().isRewardBound()) {
                 STORM_LOG_THROW(checkTask.isOnlyInitialStatesRelevantSet(), storm::exceptions::InvalidOperationException, "Checking reward bounded cumulative reward formulas can only be done for the initial states of the model.");
+                STORM_LOG_THROW(checkTask.getFormula().hasRewardAccumulation(), storm::exceptions::InvalidOperationException, "Checking reward bounded cumulative reward formulas is not supported if reward accumulations are given.");
                 STORM_LOG_WARN_COND(!checkTask.isQualitativeSet(), "Checking reward bounded until formulas is not optimized w.r.t. qualitative queries");
                 storm::logic::OperatorInformation opInfo(checkTask.getOptimizationDirection());
                 if (checkTask.isBoundSet()) {
@@ -151,7 +153,8 @@ namespace storm {
                 return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(std::move(numericResult)));
             } else {
                 STORM_LOG_THROW(rewardPathFormula.hasIntegerBound(), storm::exceptions::InvalidPropertyException, "Formula needs to have a discrete time bound.");
-                std::vector<ValueType> numericResult = storm::modelchecker::helper::SparseMdpPrctlHelper<ValueType>::computeCumulativeRewards(env, storm::solver::SolveGoal<ValueType>(this->getModel(), checkTask), this->getModel().getTransitionMatrix(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""), rewardPathFormula.getNonStrictBound<uint64_t>());
+                auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+                std::vector<ValueType> numericResult = storm::modelchecker::helper::SparseMdpPrctlHelper<ValueType>::computeCumulativeRewards(env, storm::solver::SolveGoal<ValueType>(this->getModel(), checkTask), this->getModel().getTransitionMatrix(), rewardModel.get(), rewardPathFormula.getNonStrictBound<uint64_t>());
                 return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(std::move(numericResult)));
             }
         }
@@ -171,7 +174,8 @@ namespace storm {
             STORM_LOG_THROW(checkTask.isOptimizationDirectionSet(), storm::exceptions::InvalidPropertyException, "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model.");
             std::unique_ptr<CheckResult> subResultPointer = this->check(env, eventuallyFormula.getSubformula());
             ExplicitQualitativeCheckResult const& subResult = subResultPointer->asExplicitQualitativeCheckResult();
-            auto ret = storm::modelchecker::helper::SparseMdpPrctlHelper<ValueType>::computeReachabilityRewards(env, storm::solver::SolveGoal<ValueType>(this->getModel(), checkTask), this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""), subResult.getTruthValuesVector(), checkTask.isQualitativeSet(), checkTask.isProduceSchedulersSet(), checkTask.getHint());
+            auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+            auto ret = storm::modelchecker::helper::SparseMdpPrctlHelper<ValueType>::computeReachabilityRewards(env, storm::solver::SolveGoal<ValueType>(this->getModel(), checkTask), this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), rewardModel.get(), subResult.getTruthValuesVector(), checkTask.isQualitativeSet(), checkTask.isProduceSchedulersSet(), checkTask.getHint());
             std::unique_ptr<CheckResult> result(new ExplicitQuantitativeCheckResult<ValueType>(std::move(ret.values)));
             if (checkTask.isProduceSchedulersSet() && ret.scheduler) {
                 result->asExplicitQuantitativeCheckResult<ValueType>().setScheduler(std::move(ret.scheduler));
@@ -196,7 +200,8 @@ namespace storm {
         template<typename SparseMdpModelType>
         std::unique_ptr<CheckResult> SparseMdpPrctlModelChecker<SparseMdpModelType>::computeTotalRewards(Environment const& env, storm::logic::RewardMeasureType, CheckTask<storm::logic::TotalRewardFormula, ValueType> const& checkTask) {
             STORM_LOG_THROW(checkTask.isOptimizationDirectionSet(), storm::exceptions::InvalidPropertyException, "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model.");
-            auto ret = storm::modelchecker::helper::SparseMdpPrctlHelper<ValueType>::computeTotalRewards(env, storm::solver::SolveGoal<ValueType>(this->getModel(), checkTask), this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""), checkTask.isQualitativeSet(), checkTask.isProduceSchedulersSet(), checkTask.getHint());
+            auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+            auto ret = storm::modelchecker::helper::SparseMdpPrctlHelper<ValueType>::computeTotalRewards(env, storm::solver::SolveGoal<ValueType>(this->getModel(), checkTask), this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), rewardModel.get(), checkTask.isQualitativeSet(), checkTask.isProduceSchedulersSet(), checkTask.getHint());
             std::unique_ptr<CheckResult> result(new ExplicitQuantitativeCheckResult<ValueType>(std::move(ret.values)));
             if (checkTask.isProduceSchedulersSet() && ret.scheduler) {
                 result->asExplicitQuantitativeCheckResult<ValueType>().setScheduler(std::move(ret.scheduler));
@@ -217,7 +222,8 @@ namespace storm {
         template<typename SparseMdpModelType>
         std::unique_ptr<CheckResult> SparseMdpPrctlModelChecker<SparseMdpModelType>::computeLongRunAverageRewards(Environment const& env, storm::logic::RewardMeasureType rewardMeasureType, CheckTask<storm::logic::LongRunAverageRewardFormula, ValueType> const& checkTask) {
             STORM_LOG_THROW(checkTask.isOptimizationDirectionSet(), storm::exceptions::InvalidPropertyException, "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model.");
-            std::vector<ValueType> result = storm::modelchecker::helper::SparseMdpPrctlHelper<ValueType>::computeLongRunAverageRewards(env, storm::solver::SolveGoal<ValueType>(this->getModel(), checkTask), this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getUniqueRewardModel());
+            auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+            std::vector<ValueType> result = storm::modelchecker::helper::SparseMdpPrctlHelper<ValueType>::computeLongRunAverageRewards(env, storm::solver::SolveGoal<ValueType>(this->getModel(), checkTask), this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), rewardModel.get());
             return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(std::move(result)));
         }
         
diff --git a/src/storm/modelchecker/prctl/SymbolicDtmcPrctlModelChecker.cpp b/src/storm/modelchecker/prctl/SymbolicDtmcPrctlModelChecker.cpp
index a6a099833..8b0040b2f 100644
--- a/src/storm/modelchecker/prctl/SymbolicDtmcPrctlModelChecker.cpp
+++ b/src/storm/modelchecker/prctl/SymbolicDtmcPrctlModelChecker.cpp
@@ -5,6 +5,7 @@
 #include "storm/storage/dd/Add.h"
 
 #include "storm/utility/macros.h"
+#include "storm/utility/FilteredRewardModel.h"
 
 #include "storm/models/symbolic/StandardRewardModel.h"
 
@@ -30,7 +31,7 @@ namespace storm {
         template<typename ModelType>
         bool SymbolicDtmcPrctlModelChecker<ModelType>::canHandle(CheckTask<storm::logic::Formula, ValueType> const& checkTask) const {
             storm::logic::Formula const& formula = checkTask.getFormula();
-            return formula.isInFragment(storm::logic::prctl().setLongRunAverageRewardFormulasAllowed(false).setTimeOperatorsAllowed(true).setReachbilityTimeFormulasAllowed(true));
+            return formula.isInFragment(storm::logic::prctl().setLongRunAverageRewardFormulasAllowed(false).setTimeOperatorsAllowed(true).setReachbilityTimeFormulasAllowed(true).setRewardAccumulationAllowed(true));
         }
         
         template<typename ModelType>
@@ -79,7 +80,8 @@ namespace storm {
         std::unique_ptr<CheckResult> SymbolicDtmcPrctlModelChecker<ModelType>::computeCumulativeRewards(Environment const& env, storm::logic::RewardMeasureType, CheckTask<storm::logic::CumulativeRewardFormula, ValueType> const& checkTask) {
             storm::logic::CumulativeRewardFormula const& rewardPathFormula = checkTask.getFormula();
             STORM_LOG_THROW(rewardPathFormula.hasIntegerBound(), storm::exceptions::InvalidPropertyException, "Formula needs to have a discrete time bound.");
-            storm::dd::Add<DdType, ValueType> numericResult = storm::modelchecker::helper::SymbolicDtmcPrctlHelper<DdType, ValueType>::computeCumulativeRewards(env, this->getModel(), this->getModel().getTransitionMatrix(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""), rewardPathFormula.getNonStrictBound<uint64_t>());
+            auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+            storm::dd::Add<DdType, ValueType> numericResult = storm::modelchecker::helper::SymbolicDtmcPrctlHelper<DdType, ValueType>::computeCumulativeRewards(env, this->getModel(), this->getModel().getTransitionMatrix(), rewardModel.get(), rewardPathFormula.getNonStrictBound<uint64_t>());
             return std::unique_ptr<SymbolicQuantitativeCheckResult<DdType, ValueType>>(new SymbolicQuantitativeCheckResult<DdType, ValueType>(this->getModel().getReachableStates(), numericResult));
         }
         
@@ -96,7 +98,8 @@ namespace storm {
             storm::logic::EventuallyFormula const& eventuallyFormula = checkTask.getFormula();
             std::unique_ptr<CheckResult> subResultPointer = this->check(env, eventuallyFormula.getSubformula());
             SymbolicQualitativeCheckResult<DdType> const& subResult = subResultPointer->asSymbolicQualitativeCheckResult<DdType>();
-            storm::dd::Add<DdType, ValueType> numericResult = storm::modelchecker::helper::SymbolicDtmcPrctlHelper<DdType, ValueType>::computeReachabilityRewards(env, this->getModel(), this->getModel().getTransitionMatrix(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""), subResult.getTruthValuesVector(), checkTask.isQualitativeSet());
+            auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+            storm::dd::Add<DdType, ValueType> numericResult = storm::modelchecker::helper::SymbolicDtmcPrctlHelper<DdType, ValueType>::computeReachabilityRewards(env, this->getModel(), this->getModel().getTransitionMatrix(), rewardModel.get(), subResult.getTruthValuesVector(), checkTask.isQualitativeSet());
             return std::make_unique<SymbolicQuantitativeCheckResult<DdType, ValueType>>(this->getModel().getReachableStates(), numericResult);
         }
 
diff --git a/src/storm/modelchecker/prctl/SymbolicMdpPrctlModelChecker.cpp b/src/storm/modelchecker/prctl/SymbolicMdpPrctlModelChecker.cpp
index 713ce3295..a08546669 100644
--- a/src/storm/modelchecker/prctl/SymbolicMdpPrctlModelChecker.cpp
+++ b/src/storm/modelchecker/prctl/SymbolicMdpPrctlModelChecker.cpp
@@ -11,6 +11,7 @@
 
 #include "storm/utility/macros.h"
 #include "storm/utility/graph.h"
+#include "storm/utility/FilteredRewardModel.h"
 
 #include "storm/settings/modules/GeneralSettings.h"
 
@@ -30,7 +31,7 @@ namespace storm {
         template<typename ModelType>
         bool SymbolicMdpPrctlModelChecker<ModelType>::canHandle(CheckTask<storm::logic::Formula, ValueType> const& checkTask) const {
             storm::logic::Formula const& formula = checkTask.getFormula();
-            return formula.isInFragment(storm::logic::prctl().setLongRunAverageRewardFormulasAllowed(false).setTimeOperatorsAllowed(true).setReachbilityTimeFormulasAllowed(true));
+            return formula.isInFragment(storm::logic::prctl().setLongRunAverageRewardFormulasAllowed(false).setTimeOperatorsAllowed(true).setReachbilityTimeFormulasAllowed(true).setRewardAccumulationAllowed(true));
         }
         
         template<typename ModelType>
@@ -80,7 +81,8 @@ namespace storm {
             storm::logic::CumulativeRewardFormula const& rewardPathFormula = checkTask.getFormula();
             STORM_LOG_THROW(checkTask.isOptimizationDirectionSet(), storm::exceptions::InvalidArgumentException, "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model.");
             STORM_LOG_THROW(rewardPathFormula.hasIntegerBound(), storm::exceptions::InvalidPropertyException, "Formula needs to have a discrete time bound.");
-            return storm::modelchecker::helper::SymbolicMdpPrctlHelper<DdType, ValueType>::computeCumulativeRewards(env, checkTask.getOptimizationDirection(), this->getModel(), this->getModel().getTransitionMatrix(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""), rewardPathFormula.getNonStrictBound<uint64_t>());
+            auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+            return storm::modelchecker::helper::SymbolicMdpPrctlHelper<DdType, ValueType>::computeCumulativeRewards(env, checkTask.getOptimizationDirection(), this->getModel(), this->getModel().getTransitionMatrix(), rewardModel.get(), rewardPathFormula.getNonStrictBound<uint64_t>());
         }
         
         template<typename ModelType>
@@ -97,7 +99,8 @@ namespace storm {
             STORM_LOG_THROW(checkTask.isOptimizationDirectionSet(), storm::exceptions::InvalidPropertyException, "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model.");
             std::unique_ptr<CheckResult> subResultPointer = this->check(env, eventuallyFormula.getSubformula());
             SymbolicQualitativeCheckResult<DdType> const& subResult = subResultPointer->asSymbolicQualitativeCheckResult<DdType>();
-            return storm::modelchecker::helper::SymbolicMdpPrctlHelper<DdType, ValueType>::computeReachabilityRewards(env, checkTask.getOptimizationDirection(), this->getModel(), this->getModel().getTransitionMatrix(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""), subResult.getTruthValuesVector());
+            auto rewardModel = storm::utility::createFilteredRewardModel(this->getModel(), checkTask);
+            return storm::modelchecker::helper::SymbolicMdpPrctlHelper<DdType, ValueType>::computeReachabilityRewards(env, checkTask.getOptimizationDirection(), this->getModel(), this->getModel().getTransitionMatrix(), rewardModel.get(), subResult.getTruthValuesVector());
         }
         
         template<typename ModelType>
diff --git a/src/storm/utility/FilteredRewardModel.h b/src/storm/utility/FilteredRewardModel.h
new file mode 100644
index 000000000..32dc13521
--- /dev/null
+++ b/src/storm/utility/FilteredRewardModel.h
@@ -0,0 +1,64 @@
+#pragma once
+
+#include <memory>
+
+#include "storm/utility/macros.h"
+#include "storm/exceptions/NotSupportedException.h"
+
+namespace storm {
+    namespace utility {
+        
+        
+        /*
+         * This class wraps around a
+         */
+        template <typename RewardModelType>
+        class FilteredRewardModel {
+        public:
+            FilteredRewardModel(RewardModelType const& baseRewardModel, bool enableStateRewards, bool enableStateActionRewards, bool enableTransitionRewards) {
+                if ((baseRewardModel.hasStateRewards() && !enableStateRewards) || (baseRewardModel.hasStateActionRewards() && !enableStateActionRewards) || (baseRewardModel.hasTransitionRewards() && !enableTransitionRewards)) {
+                    // One of the available reward types need to be deleted.
+                    typename std::remove_const<typename std::remove_reference<decltype(baseRewardModel.getOptionalStateRewardVector())>::type>::type stateRewards;
+                    if (enableStateRewards) {
+                        stateRewards = baseRewardModel.getOptionalStateRewardVector();
+                    }
+                    typename std::remove_const<typename std::remove_reference<decltype(baseRewardModel.getOptionalStateActionRewardVector())>::type>::type stateActionRewards;
+                    if (enableStateActionRewards) {
+                        stateActionRewards = baseRewardModel.getOptionalStateActionRewardVector();
+                    }
+                    typename std::remove_const<typename std::remove_reference<decltype(baseRewardModel.getOptionalTransitionRewardMatrix())>::type>::type transitionRewards;
+                    if (enableTransitionRewards) {
+                        transitionRewards = baseRewardModel.getOptionalTransitionRewardMatrix();
+                    }
+                    localRewardModel = std::unique_ptr<RewardModelType>(new RewardModelType(stateRewards, stateActionRewards, transitionRewards));
+                    rewardModel = localRewardModel.get();
+                } else {
+                    rewardModel = &baseRewardModel;
+                }
+            }
+
+            RewardModelType const& get() const {
+                return *rewardModel;
+            }
+        private:
+                std::unique_ptr<RewardModelType> localRewardModel;
+                RewardModelType const* rewardModel;
+        };
+        
+        template <typename ModelType, typename CheckTaskType>
+        FilteredRewardModel<typename ModelType::RewardModelType> createFilteredRewardModel(ModelType const& model, CheckTaskType const& checkTask) {
+            auto const& baseRewardModel = checkTask.isRewardModelSet() ? model.getRewardModel(checkTask.getRewardModel()) : model.getUniqueRewardModel();
+            if (checkTask.getFormula().hasRewardAccumulation()) {
+                auto const& acc = checkTask.getFormula().getRewardAccumulation();
+                STORM_LOG_THROW(model.isDiscreteTimeModel() || !acc.isExitSet() || !baseRewardModel.hasStateRewards(), storm::exceptions::NotSupportedException, "Exit rewards for continuous time models are not supported.");
+                // Check which of the available reward types are allowed.
+                bool hasStateRewards = model.isDiscreteTimeModel() ? acc.isExitSet() : acc.isTimeSet();
+                bool hasStateActionRewards = acc.isStepsSet();
+                bool hasTransitionRewards = acc.isStepsSet();
+                return FilteredRewardModel<typename ModelType::RewardModelType>(baseRewardModel, hasStateRewards, hasStateActionRewards, hasTransitionRewards);
+            } else {
+                return FilteredRewardModel<typename ModelType::RewardModelType>(baseRewardModel, true, true, true);
+            }
+        }
+    }
+}
\ No newline at end of file