diff --git a/fancy_gym/black_box/black_box_wrapper.py b/fancy_gym/black_box/black_box_wrapper.py
index dc3d0d5..a73915e 100644
--- a/fancy_gym/black_box/black_box_wrapper.py
+++ b/fancy_gym/black_box/black_box_wrapper.py
@@ -22,6 +22,7 @@ class BlackBoxWrapper(gym.ObservationWrapper):
                  replanning_schedule: Optional[
                      Callable[[np.ndarray, np.ndarray, np.ndarray, np.ndarray, int], bool]] = None,
                  reward_aggregation: Callable[[np.ndarray], float] = np.sum,
+                 max_replan_times: int = 1,
                  desired_conditioning: bool = False
                  ):
         """
@@ -73,6 +74,9 @@ class BlackBoxWrapper(gym.ObservationWrapper):
         self.condition_pos = None
         self.condition_vel = None
 
+        self.max_replan_times = max_replan_times
+        self.replan_counts = 0
+
     def observation(self, observation):
         # return context space if we are
         if self.return_context_observation:
@@ -155,6 +159,7 @@ class BlackBoxWrapper(gym.ObservationWrapper):
         infos = dict()
         done = False
 
+        self.replan_counts += 1
         for t, (pos, vel) in enumerate(zip(position, velocity)):
             step_action = self.tracking_controller.get_action(pos, vel, self.current_pos, self.current_vel)
             c_action = np.clip(step_action, self.env.action_space.low, self.env.action_space.high)
@@ -173,14 +178,16 @@ class BlackBoxWrapper(gym.ObservationWrapper):
             if self.render_kwargs:
                 self.env.render(**self.render_kwargs)
 
-            if done or self.replanning_schedule(self.current_pos, self.current_vel, obs, c_action,
-                                                t + 1 + self.current_traj_steps):
+            if done or (self.replan_counts < self.max_replan_times
+                        and self.replanning_schedule(self.current_pos, self.current_vel, obs, c_action,
+                                                t + 1 + self.current_traj_steps)):
                 if self.desired_conditioning:
                     self.condition_pos = pos
                     self.condition_vel = vel
                 else:
                     self.condition_pos = self.current_pos
                     self.condition_vel = self.current_vel
+
                 break
 
         infos.update({k: v[:t+1] for k, v in infos.items()})
diff --git a/fancy_gym/envs/__init__.py b/fancy_gym/envs/__init__.py
index d38194b..e2bea2e 100644
--- a/fancy_gym/envs/__init__.py
+++ b/fancy_gym/envs/__init__.py
@@ -498,11 +498,12 @@ for _v in _versions:
     kwargs_dict_box_pushing_prodmp['controller_kwargs']['d_gains'] = 0.01 * np.array([10., 10., 10., 10., 6., 5., 3.])
     # kwargs_dict_box_pushing_prodmp['trajectory_generator_kwargs']['weights_scale'] = np.array([3.4944e+01, 4.3734e+01, 9.6711e+01, 2.4429e+02, 5.8272e+02])
     # kwargs_dict_box_pushing_prodmp['trajectory_generator_kwargs']['goal_scale'] = 3.1264e-01
-    kwargs_dict_box_pushing_prodmp['trajectory_generator_kwargs']['weights_scale'] = np.array([100., 166., 500., 1000.])
-    kwargs_dict_box_pushing_prodmp['trajectory_generator_kwargs']['goal_scale'] = 1.
+    kwargs_dict_box_pushing_prodmp['trajectory_generator_kwargs']['weights_scale'] = 0.3 * np.array([100., 166., 500., 1000.])
+    kwargs_dict_box_pushing_prodmp['trajectory_generator_kwargs']['goal_scale'] = 0.3 * 1.
     kwargs_dict_box_pushing_prodmp['basis_generator_kwargs']['num_basis'] = 4
     kwargs_dict_box_pushing_prodmp['basis_generator_kwargs']['alpha'] = 10.
-    kwargs_dict_box_pushing_prodmp['black_box_kwargs']['replanning_schedule'] = lambda pos, vel, obs, action, t: t % 25 == 0
+    kwargs_dict_box_pushing_prodmp['black_box_kwargs']['max_replan_times'] = 4
+    kwargs_dict_box_pushing_prodmp['black_box_kwargs']['replanning_schedule'] = lambda pos, vel, obs, action, t : t % 25 == 0
     register(
         id=_env_id,
         entry_point='fancy_gym.utils.make_env_helpers:make_bb_env_helper',
diff --git a/test/test_replanning_envs.py b/test/test_replanning_envs.py
index 227e885..c6d697e 100644
--- a/test/test_replanning_envs.py
+++ b/test/test_replanning_envs.py
@@ -9,7 +9,15 @@ Fancy_ProDMP_IDS = fancy_gym.ALL_FANCY_MOVEMENT_PRIMITIVE_ENVIRONMENTS['ProDMP']
 
 All_ProDMP_IDS = fancy_gym.ALL_MOVEMENT_PRIMITIVE_ENVIRONMENTS['ProDMP']
 
+
+
 @pytest.mark.parametrize('env_id', Fancy_ProDMP_IDS)
-def test_prodmp_envs(env_id: str):
+def test_replanning_envs(env_id: str):
     """Tests that ProDMP environments run without errors using random actions."""
-    run_env(env_id)
\ No newline at end of file
+    run_env(env_id, iterations=4)
+
+# @pytest.mark.parametrize('env_id', All_ProDMP_IDS)
+# def test_replanning_determinism(env_id: str):
+#     """Tests that ProDMP environments are deterministic."""
+#     run_env_determinism(env_id, 0)
+