diff --git a/examples/simulator/02-simulator.py b/examples/simulator/02-simulator.py
index 35362b5..e23a0da 100644
--- a/examples/simulator/02-simulator.py
+++ b/examples/simulator/02-simulator.py
@@ -9,7 +9,7 @@ import random
 """
 Simulator for nondeterministic models
 """
-def example_simulator_01():
+def example_simulator_02():
     path = stormpy.examples.files.prism_mdp_maze
     prism_program = stormpy.parse_prism_program(path)
 
@@ -36,7 +36,36 @@ def example_simulator_01():
     for path in paths:
         print(" ".join(path))
 
+    options = stormpy.BuilderOptions()
+    options.set_build_state_valuations()
+    options.set_build_choice_labels(True)
+    model = stormpy.build_sparse_model_with_options(prism_program, options)
+    print(model)
+    simulator = stormpy.simulator.create_simulator(model, seed=42)
+    simulator.set_observation_mode(stormpy.simulator.SimulatorObservationMode.PROGRAM_LEVEL)
+    simulator.set_action_mode(stormpy.simulator.SimulatorActionMode.GLOBAL_NAMES)
+    # 5 paths of at most 20 steps.
+    paths = []
+    for m in range(5):
+        path = []
+        state = simulator.restart()
+        path = [f"{state}"]
+        for n in range(20):
+            actions = simulator.available_actions()
+            select_action = random.randint(0,len(actions)-1)
+            #print(f"Randomly select action nr: {select_action} from actions {actions}")
+            path.append(f"--act={actions[select_action]}-->")
+            state = simulator.step(actions[select_action])
+            #print(state)
+            path.append(f"{state}")
+            if simulator.is_done():
+                #print("Trapped!")
+                break
+        paths.append(path)
+    for path in paths:
+        print(" ".join(path))
+
 
 
 if __name__ == '__main__':
-    example_simulator_01()
+    example_simulator_02()
diff --git a/lib/stormpy/simulator.py b/lib/stormpy/simulator.py
index f154673..8c90916 100644
--- a/lib/stormpy/simulator.py
+++ b/lib/stormpy/simulator.py
@@ -8,7 +8,8 @@ class SimulatorObservationMode(Enum):
     PROGRAM_LEVEL = 1
 
 class SimulatorActionMode(Enum):
-    INDEX_LEVEL = 0
+    INDEX_LEVEL = 0,
+    GLOBAL_NAMES = 1
 
 class Simulator:
     """
@@ -62,6 +63,11 @@ class Simulator:
             raise RuntimeError("Observation mode must be a SimulatorObservationMode")
         self._observation_mode = mode
 
+    def set_action_mode(self, mode):
+        if not isinstance(mode, SimulatorActionMode):
+            raise RuntimeError("Action mode must be a SimulatorActionMode")
+        self._action_mode = mode
+
     def set_full_observability(self, value):
         """
         Sets whether the full state space is observable.
@@ -87,7 +93,22 @@ class SparseSimulator(Simulator):
         self.set_full_observability(self._model.model_type != stormpy.storage.ModelType.POMDP)
 
     def available_actions(self):
-        return range(self.nr_available_actions())
+        if self._action_mode == SimulatorActionMode.INDEX_LEVEL:
+            return range(self.nr_available_actions())
+        else:
+            assert self._model.has_choice_labeling(), "Global names require choice labeling"
+            av_actions = []
+            current_state = self._engine.get_current_state()
+            for action_offset in range(self.nr_available_actions()):
+                choice_label = self._model.choice_labeling.get_labels_of_choice(self._model.get_choice_index(current_state, action_offset))
+                if len(choice_label) == 0:
+                    av_actions.append(f"_act_{action_offset}")
+                elif len(choice_label) == 1:
+                    av_actions.append(list(choice_label)[0])
+                else:
+                    assert False, "Unknown type of choice label, support not implemented"
+
+            return av_actions
 
     def nr_available_actions(self):
         return self._model.get_nr_available_actions(self._engine.get_current_state())
@@ -123,11 +144,25 @@ class SparseSimulator(Simulator):
                 raise RuntimeError("Must specify an action in nondeterministic models.")
             check = self._engine.step(0)
             assert check
-        else:
+        elif type(action) == int and self._action_mode == SimulatorActionMode.INDEX_LEVEL:
             if action >= self.nr_available_actions():
                 raise RuntimeError(f"Only {self.nr_available_actions()} actions available")
             check = self._engine.step(action)
             assert check
+        elif self._action_mode == SimulatorActionMode.GLOBAL_NAMES:
+            current_state = self._engine.get_current_state()
+            action_index = None
+            av_actions = self.available_actions()
+            for offset, label in enumerate(av_actions):
+                if action == label:
+                    action_index = offset
+                    break
+            if action_index is None:
+                raise ValueError("Could not find action: ")
+            check = self._engine.step(action_index)
+            assert check
+        else:
+            raise ValueError("Unrecognized type of action %s" % action)
         return self._report_result()