diff --git a/sbBrix/common/off_policy_algorithm.py b/sbBrix/common/off_policy_algorithm.py
index 816d033..0720e33 100644
--- a/sbBrix/common/off_policy_algorithm.py
+++ b/sbBrix/common/off_policy_algorithm.py
@@ -498,13 +498,13 @@ class BetterOffPolicyAlgorithm(OffPolicyAlgorithm):
         if action_noise is not None and env.num_envs > 1 and not isinstance(action_noise, VectorizedActionNoise):
             action_noise = VectorizedActionNoise(action_noise, env.num_envs)
 
-        if self.use_sde:
+        if self.use_sde or self.use_pca:
             self.actor.reset_noise(env.num_envs)
 
         callback.on_rollout_start()
         continue_training = True
         while should_collect_more_steps(train_freq, num_collected_steps, num_collected_episodes):
-            if self.use_sde and self.sde_sample_freq > 0 and num_collected_steps % self.sde_sample_freq == 0:
+            if (self.use_sde or self.use_pca) and self.sde_sample_freq > 0 and num_collected_steps % self.sde_sample_freq == 0:
                 # Sample a new noise matrix
                 self.actor.reset_noise(env.num_envs)
 
diff --git a/sbBrix/common/policies.py b/sbBrix/common/policies.py
index 67fc963..771ae0f 100644
--- a/sbBrix/common/policies.py
+++ b/sbBrix/common/policies.py
@@ -548,8 +548,10 @@ class ActorCriticPolicy(BasePolicy):
 
         :param n_envs:
         """
-        assert isinstance(self.action_dist, StateDependentNoiseDistribution), "reset_noise() is only available when using gSDE"
-        self.action_dist.sample_weights(self.log_std, batch_size=n_envs)
+        if isinstance(self.action_dist, StateDependentNoiseDistribution):
+            self.action_dist.sample_weights(self.log_std, batch_size=n_envs)
+        else:
+            self.action_dist.base_noise.reset()
 
     def _build_mlp_extractor(self) -> None:
         """
@@ -887,8 +889,10 @@ class Actor(BasePolicy):
         :param batch_size:
         """
         msg = "reset_noise() is only available when using gSDE"
-        assert isinstance(self.action_dist, StateDependentNoiseDistribution), msg
-        self.action_dist.sample_weights(self.log_std, batch_size=batch_size)
+        if isinstance(self.action_dist, StateDependentNoiseDistribution):
+            self.action_dist.sample_weights(self.log_std, batch_size=batch_size)
+        else:
+            self.action_dist.base_noise.reset()
 
     def get_action_dist_params(self, obs: th.Tensor) -> Tuple[th.Tensor, th.Tensor, Dict[str, th.Tensor]]:
         """
@@ -1083,7 +1087,10 @@ class SACPolicy(BasePolicy):
 
         :param batch_size:
         """
-        self.actor.reset_noise(batch_size=batch_size)
+        if isinstance(self.action_space, StateDependentNoiseDistribution):
+            self.actor.reset_noise(batch_size=batch_size)
+        else:
+            self.actor.reset_noise(batch_size=batch_size)
 
     def make_actor(self, features_extractor: Optional[BaseFeaturesExtractor] = None) -> Actor:
         actor_kwargs = self._update_features_extractor(self.actor_kwargs, features_extractor)
diff --git a/sbBrix/ppo/ppo.py b/sbBrix/ppo/ppo.py
index 0181975..b3ff5f1 100644
--- a/sbBrix/ppo/ppo.py
+++ b/sbBrix/ppo/ppo.py
@@ -208,7 +208,7 @@ class PPO(BetterOnPolicyAlgorithm):
                     actions = rollout_data.actions.long().flatten()
 
                 # Re-sample the noise matrix because the log_std has changed
-                if self.use_sde:
+                if self.use_sde or self.use_pca:
                     self.policy.reset_noise(self.batch_size)
 
                 values, log_prob, entropy = self.policy.evaluate_actions(rollout_data.observations, actions)