diff --git a/agents/agent.py b/agents/agent.py
index 0279efd..d6978bc 100644
--- a/agents/agent.py
+++ b/agents/agent.py
@@ -100,8 +100,12 @@ class Agent:
 
         if self.tp.env.normalize_observation and not self.env.is_state_type_image:
             if not self.tp.distributed or not self.tp.agent.share_statistics_between_workers:
-                self.running_observation_stats = RunningStat((self.tp.env.desired_observation_width,))
-                self.running_reward_stats = RunningStat(())
+                if self.tp.checkpoint_restore_dir:
+                    checkpoint_path = os.path.join(self.tp.checkpoint_restore_dir, "running_stats.p")
+                    self.running_observation_stats = read_pickle(checkpoint_path)
+                else:
+                    self.running_observation_stats = RunningStat((self.tp.env.desired_observation_width,))
+                    self.running_reward_stats = RunningStat(())
             else:
                 self.running_observation_stats = SharedRunningStats(self.tp, replicated_device,
                                                                     shape=(self.tp.env.desired_observation_width,),
@@ -515,6 +519,9 @@ class Agent:
                 if current_snapshot_period > model_snapshots_periods_passed:
                     model_snapshots_periods_passed = current_snapshot_period
                     self.main_network.save_model(model_snapshots_periods_passed)
+                    to_pickle(self.running_observation_stats,
+                              os.path.join(self.tp.save_model_dir,
+                                           "running_stats.p".format(model_snapshots_periods_passed)))
 
             # play and record in replay buffer
             if self.tp.agent.step_until_collecting_full_episodes:
diff --git a/configurations.py b/configurations.py
index aff718a..2fefd45 100644
--- a/configurations.py
+++ b/configurations.py
@@ -442,7 +442,7 @@ class ClippedPPO(AgentParameters):
     batch_size = 64
     use_separate_networks_per_head = True
     step_until_collecting_full_episodes = True
-    beta_entropy = 0.01
+    beta_entropy = 0.001
 
 class DFP(AgentParameters):
     type = 'DFPAgent'