diff --git a/configs/architecture/decentralized.yaml b/configs/architecture/decentralized.yaml
index 9e3ae53..70b0fb2 100644
--- a/configs/architecture/decentralized.yaml
+++ b/configs/architecture/decentralized.yaml
@@ -29,4 +29,4 @@ critic:
 message_passing_steps: 4
 
 # Connectivity topology (e.g., ring, fully_connected)
-topology_type: "ring"
+topology_type: "fully_connected"
diff --git a/configs/morphology/2_arms_decentralized.yaml b/configs/morphology/2_arms_decentralized.yaml
new file mode 100644
index 0000000..9fe3160
--- /dev/null
+++ b/configs/morphology/2_arms_decentralized.yaml
@@ -0,0 +1,6 @@
+# 2 Arms Morphology Configuration
+
+segments_per_arm: [4, 0, 4, 0, 0]
+use_p_control: true
+use_torque_control: false
+morph_mode: FULLY_CONNECTED
\ No newline at end of file
diff --git a/scripts/train.py b/scripts/train.py
index 8e61bd0..f82d6bc 100644
--- a/scripts/train.py
+++ b/scripts/train.py
@@ -42,7 +42,7 @@ def main(dict_cfg: DictConfig):
         base_dir=os.path.dirname(run_dir),
     )
     logger = get_logger()
-    logger.set_level(logging.DEBUG)
+    logger.set_level(logging.INFO)
     logger.info(f"Hydra-initialized run: {run_name}")
     logger.info(f"Output directory: {run_dir}")
 
diff --git a/src/brittle_star_project/trainers/PPOTrainer.py b/src/brittle_star_project/trainers/PPOTrainer.py
index fef6f1c..72c4734 100644
--- a/src/brittle_star_project/trainers/PPOTrainer.py
+++ b/src/brittle_star_project/trainers/PPOTrainer.py
@@ -221,10 +221,15 @@ def _get_action_and_value_noise(
     adj_matrix: jnp.ndarray,
 ):
     def apply_message_passing(h):
+        assert message_passer is not None, (
+            "message passing shouldn't be performed if morphology mode is Centralized"
+        )
+
         return message_passer.apply(agent_state.params["message_passer_params"], h, adj_matrix)
 
     hidden = apply_per_node(sensor, agent_state.params["sensor_params"], next_obs)
-    hidden = jax.vmap(apply_message_passing)(hidden)
+    if message_passer is not None:
+        hidden = jax.vmap(apply_message_passing)(hidden)
 
     hidden_critic = apply_shared(
         feature_extractor, agent_state.params["feature_extractor_params"], next_obs