diff --git a/gym_pybullet_drones/envs/BaseRLAviary.py b/gym_pybullet_drones/envs/BaseRLAviary.py
index e6988e5df..0c2549822 100644
--- a/gym_pybullet_drones/envs/BaseRLAviary.py
+++ b/gym_pybullet_drones/envs/BaseRLAviary.py
@@ -62,8 +62,8 @@ def __init__(self,
             The type of action space (1 or 3D; RPMS, thurst and torques, waypoint or velocity with PID control; etc.)
 
         """
-        #### Create a buffer for the last 10 actions ###############
-        self.ACTION_BUFFER_SIZE = 10
+        #### Create a buffer for the last .5 sec of actions ########
+        self.ACTION_BUFFER_SIZE = int(ctrl_freq//2)
         self.action_buffer = deque(maxlen=self.ACTION_BUFFER_SIZE)
         ####
         vision_attributes = True if obs == ObservationType.RGB else False
diff --git a/gym_pybullet_drones/envs/HoverAviary.py b/gym_pybullet_drones/envs/HoverAviary.py
index 449a37a57..927504036 100644
--- a/gym_pybullet_drones/envs/HoverAviary.py
+++ b/gym_pybullet_drones/envs/HoverAviary.py
@@ -107,8 +107,8 @@ def _computeTruncated(self):
 
         """
         state = self._getDroneStateVector(0)
-        if (abs(state[0]) > 2.0 or abs(state[1]) > 2.0 or state[2] > 2.0 # Truncate when the drone is too far away
-             or abs(state[7]) > .5 or abs(state[8]) > .5 # Truncate when the drone is too tilted
+        if (abs(state[0]) > 1.5 or abs(state[1]) > 1.5 or state[2] > 2.0 # Truncate when the drone is too far away
+             or abs(state[7]) > .4 or abs(state[8]) > .4 # Truncate when the drone is too tilted
         ):
             return True
         if self.step_counter/self.PYB_FREQ > self.EPISODE_LEN_SEC:
diff --git a/gym_pybullet_drones/envs/MultiHoverAviary.py b/gym_pybullet_drones/envs/MultiHoverAviary.py
index 6a8db25d5..a124668c3 100644
--- a/gym_pybullet_drones/envs/MultiHoverAviary.py
+++ b/gym_pybullet_drones/envs/MultiHoverAviary.py
@@ -121,7 +121,7 @@ def _computeTruncated(self):
         states = np.array([self._getDroneStateVector(i) for i in range(self.NUM_DRONES)])
         for i in range(self.NUM_DRONES):
             if (abs(states[i][0]) > 2.0 or abs(states[i][1]) > 2.0 or states[i][2] > 2.0 # Truncate when a drones is too far away
-             or abs(states[i][7]) > .5 or abs(states[i][8]) > .5 # Truncate when a drone is too tilted
+             or abs(states[i][7]) > .4 or abs(states[i][8]) > .4 # Truncate when a drone is too tilted
             ):
                 return True
         if self.step_counter/self.PYB_FREQ > self.EPISODE_LEN_SEC:
diff --git a/gym_pybullet_drones/examples/learn.py b/gym_pybullet_drones/examples/learn.py
index 6010f9f6e..98f373753 100644
--- a/gym_pybullet_drones/examples/learn.py
+++ b/gym_pybullet_drones/examples/learn.py
@@ -76,9 +76,9 @@ def run(multiagent=DEFAULT_MA, output_folder=DEFAULT_OUTPUT_FOLDER, gui=DEFAULT_
 
     #### Target cumulative rewards (problem-dependent) ##########
     if DEFAULT_ACT == ActionType.ONE_D_RPM:
-        target_reward = 474.1 if not multiagent else 950.
+        target_reward = 474.15 if not multiagent else 949.5
     else:
-        target_reward = 465. if not multiagent else 920.
+        target_reward = 467. if not multiagent else 920.
     callback_on_best = StopTrainingOnRewardThreshold(reward_threshold=target_reward,
                                                      verbose=1)
     eval_callback = EvalCallback(eval_env,
@@ -111,9 +111,9 @@ def run(multiagent=DEFAULT_MA, output_folder=DEFAULT_OUTPUT_FOLDER, gui=DEFAULT_
     if local:
         input("Press Enter to continue...")
 
-    if os.path.isfile(filename+'/final_model.zip'):
-        path = filename+'/final_model.zip'
-    elif os.path.isfile(filename+'/best_model.zip'):
+    # if os.path.isfile(filename+'/final_model.zip'):
+    #     path = filename+'/final_model.zip'
+    if os.path.isfile(filename+'/best_model.zip'):
         path = filename+'/best_model.zip'
     else:
         print("[ERROR]: no model under the specified path", filename)