diff --git a/python/ray/actor.py b/python/ray/actor.py
index c52d7ba2a..b20da5f05 100644
--- a/python/ray/actor.py
+++ b/python/ray/actor.py
@@ -275,6 +275,13 @@ def actor(*args, **kwargs):
 
 
 def make_actor(Class, num_cpus, num_gpus):
+  # Modify the class to have an additional method that will be used for
+  # terminating the worker.
+  class Class(Class):
+    def __ray_terminate__(self):
+      import os
+      os._exit(0)
+
   class_id = random_actor_class_id()
   # The list exported will have length 0 if the class has not been exported
   # yet, and length one if it has. This is just implementing a bool, but we
@@ -389,6 +396,11 @@ def make_actor(Class, num_cpus, num_gpus):
     def __reduce__(self):
       raise Exception("Actor objects cannot be pickled.")
 
+    def __del__(self):
+      """Kill the worker that is running this actor."""
+      actor_method_call(self._ray_actor_id, "__ray_terminate__",
+                        self._ray_method_signatures["__ray_terminate__"])
+
   return NewClass
 
 
diff --git a/test/actor_test.py b/test/actor_test.py
index 65623b0d0..c250652f9 100644
--- a/test/actor_test.py
+++ b/test/actor_test.py
@@ -682,10 +682,10 @@ class ActorsWithGPUs(unittest.TestCase):
                 tuple(self.gpu_ids))
 
     # Create some actors.
-    actors = [Actor1.remote() for _ in range(num_local_schedulers * 2)]
+    actors1 = [Actor1.remote() for _ in range(num_local_schedulers * 2)]
     # Make sure that no two actors are assigned to the same GPU.
     locations_and_ids = ray.get([actor.get_location_and_ids.remote()
-                                 for actor in actors])
+                                 for actor in actors1])
     node_names = set([location for location, gpu_id in locations_and_ids])
     self.assertEqual(len(node_names), num_local_schedulers)
 
@@ -711,10 +711,10 @@ class ActorsWithGPUs(unittest.TestCase):
                 tuple(self.gpu_ids))
 
     # Create some actors.
-    actors = [Actor2.remote() for _ in range(num_local_schedulers)]
+    actors2 = [Actor2.remote() for _ in range(num_local_schedulers)]
     # Make sure that no two actors are assigned to the same GPU.
     locations_and_ids = ray.get([actor.get_location_and_ids.remote()
-                                 for actor in actors])
+                                 for actor in actors2])
     self.assertEqual(node_names,
                      set([location for location, gpu_id in locations_and_ids]))
     for location, gpu_ids in locations_and_ids:
@@ -962,10 +962,14 @@ class ActorsWithGPUs(unittest.TestCase):
         return self.gpu_ids[0]
 
     results = []
+    actors = []
     for _ in range(5):
       results.append(f.remote())
       a = Actor.remote()
       results.append(a.get_gpu_id.remote())
+      # Prevent the actor handle from going out of scope so that its GPU
+      # resources don't get released.
+      actors.append(a)
 
     gpu_ids = ray.get(results)
     self.assertEqual(set(gpu_ids), set(range(10)))