diff --git a/environments/factory/base_factory.py b/environments/factory/base_factory.py
index 00cb173..565f5a6 100644
--- a/environments/factory/base_factory.py
+++ b/environments/factory/base_factory.py
@@ -138,11 +138,12 @@ class BaseFactory(gym.Env):
     def movement_actions(self):
         return self._actions.movement_actions
 
-    def __init__(self, level='simple', n_agents=1, max_steps=int(5e2), pomdp_radius: Union[None, int] = None,
+    def __init__(self, level_name='simple', n_agents=1, max_steps=int(5e2), pomdp_radius: Union[None, int] = None,
                  movement_properties: MovementProperties = MovementProperties(),
                  omit_agent_slice_in_obs=False, **kwargs):
 
         self.movement_properties = movement_properties
+        self.level_name = level_name
 
         self.n_agents = n_agents
         self.max_steps = max_steps
@@ -154,7 +155,7 @@ class BaseFactory(gym.Env):
         self._actions = _actions + self.additional_actions
 
         self._level = h.one_hot_level(
-            h.parse_level(Path(__file__).parent / h.LEVELS_DIR / f'{level}.txt')
+            h.parse_level(Path(__file__).parent / h.LEVELS_DIR / f'{self.level_name}.txt')
         )
         self._state_slices = StateSlice(n_agents)
         if 'additional_slices' in kwargs:
@@ -328,8 +329,8 @@ class BaseFactory(gym.Env):
 
     def save_params(self, filepath: Path):
         # noinspection PyProtectedMember
-        d = {key: val._asdict() if hasattr(val, '_asdict') else val for key, val in self.__dict__.items()
-             if not key.startswith('_') and not key.startswith('__')}
+        # d = {key: val._asdict() if hasattr(val, '_asdict') else val for key, val in self.__dict__.items()
+        d = {key: val for key, val in self.__dict__.items() if not key.startswith('_') and not key.startswith('__')}
         filepath.parent.mkdir(parents=True, exist_ok=True)
 
         with filepath.open('w') as f:
diff --git a/main.py b/main.py
index ff88543..4a983fd 100644
--- a/main.py
+++ b/main.py
@@ -60,7 +60,7 @@ def compare_runs(run_path: Path, run_identifier: int, parameter: Union[str, List
                     monitor_df = pickle.load(f)
 
                 monitor_df['run'] = run
-                monitor_df['model'] = path.name.split('_')[1]
+                monitor_df['model'] = path.name.split('_')[0]
                 monitor_df = monitor_df.fillna(0)
                 df_list.append(monitor_df)
 
@@ -85,8 +85,8 @@ def compare_runs(run_path: Path, run_identifier: int, parameter: Union[str, List
 
 if __name__ == '__main__':
 
-    # compare_runs(Path('debug_out') / 'PPO_1622800949', 1622800949, 'step_reward')
-    # exit()
+    compare_runs(Path('debug_out'), 1623052687, ['agent_0_vs_level'])
+    exit()
 
     from stable_baselines3 import PPO, DQN, A2C
     from algorithms.reg_dqn import RegDQN
@@ -104,7 +104,7 @@ if __name__ == '__main__':
         for seed in range(3):
 
             env = SimpleFactory(n_agents=1, dirt_properties=dirt_props, pomdp_radius=3, max_steps=400,
-                                movement_properties=move_props, level='rooms',
+                                movement_properties=move_props, level_name='rooms',
                                 omit_agent_slice_in_obs=True)
 
             # env = FrameStack(env, 4)
@@ -112,10 +112,10 @@ if __name__ == '__main__':
             kwargs = dict(ent_coef=0.01) if isinstance(modeL_type, (PPO, A2C)) else {}
             model = modeL_type("MlpPolicy", env, verbose=1, seed=seed, device='cpu', **kwargs)
 
-            out_path = Path('debug_out') / f'{modeL_type.__class__.__name__}_{time_stamp}'
+            out_path = Path('debug_out') / f'{model.__class__.__name__}_{time_stamp}'
 
             # identifier = f'{seed}_{model.__class__.__name__}_{time_stamp}'
-            identifier = f'{seed}_{modeL_type.__class__.__name__}_{time_stamp}'
+            identifier = f'{seed}_{model.__class__.__name__}_{time_stamp}'
             out_path /= identifier
 
             callbacks = CallbackList(
@@ -127,7 +127,7 @@ if __name__ == '__main__':
             save_path = out_path / f'model_{identifier}.zip'
             save_path.parent.mkdir(parents=True, exist_ok=True)
             model.save(save_path)
-            env.save_params(out_path.parent / f'env_{model.__class__.__name__}_{time_stamp}.pick')
+            env.save_params(out_path.parent / f'env_{model.__class__.__name__}_{time_stamp}.yaml')
 
         if out_path:
             combine_runs(out_path.parent)
diff --git a/reload_agent.py b/reload_agent.py
index 0f2c46e..cfa3383 100644
--- a/reload_agent.py
+++ b/reload_agent.py
@@ -14,21 +14,21 @@ warnings.filterwarnings('ignore', category=UserWarning)
 
 if __name__ == '__main__':
 
-    model_name = 'A2C_1622650432'
+    model_name = 'PPO_1623052687'
     run_id = 0
     out_path = Path(__file__).parent / 'debug_out'
     model_path = out_path / model_name
 
-    with Path(r'C:\Users\steff\projects\f_iks\debug_out\yaml.txt').open('r') as f:
-        env_kwargs = yaml.load(f)
-    env = SimpleFactory(**env_kwargs)
+    with (model_path / f'env_{model_name}.yaml').open('r') as f:
+        env_kwargs = yaml.load(f, Loader=yaml.FullLoader)
+    env = SimpleFactory(level_name='rooms', **env_kwargs)
 
     # Edit THIS:
-    model_files = list(natsorted((model_path / f'{run_id}_{model_name}').rglob('*.zip')))
+    model_files = list(natsorted((model_path / f'{run_id}_{model_name}').rglob('model_*.zip')))
     this_model = model_files[0]
 
     model = PPO.load(this_model)
-    evaluation_result = evaluate_policy(model, env, n_eval_episodes=100, deterministic=False, render=True)
+    evaluation_result = evaluate_policy(model, env, n_eval_episodes=100, deterministic=True, render=True)
     print(evaluation_result)
 
     env.close()