diff --git a/nav_src/agent.py b/nav_src/agent.py
index 413b43d..ddcc60d 100644
--- a/nav_src/agent.py
+++ b/nav_src/agent.py
@@ -817,109 +817,3 @@ class NavGPTAgent(BaseAgent):
 
         return self.traj
 
-class RandomAgent(BaseAgent):
-    def __init__(
-            self, 
-            env: REVERIENavBatch, 
-            config: Namespace):
-        """
-        Initialize the LLM Navigation Agent.
-
-        Args:
-            env: The Matterport3D environment.
-            config: The configuration.
-        """
-        super().__init__(env)
-        self.config = config
-
-
-    def init_trajecotry(self, obs: List[dict]):
-        """Initialize the trajectory with the given observation."""
-        # Record the navigation path
-        self.traj = [{
-            'instr_id': ob['instr_id'],
-            'path': [[ob['start']]],
-            'details': [],
-        } for ob in obs]
-        # Record the history of actions taken
-
-
-    def make_equiv_action(self, actions: List[str]) -> str:
-        """
-        Interface between Panoramic view and Egocentric view
-        Take in the next viewpoint ID and move the agent to that viewpoint
-        return the turned angle and new observation
-        """
-        def normalize_angle(angle):
-            while angle > 180:
-                angle -= 360
-            while angle <= -180:
-                angle += 360
-            return angle
-
-        def angle_to_left_right(angle):
-            return f"left {-angle:.2f}" if angle < 0 else f"right {angle:.2f}"
-        
-        # Get current agent facing angle
-        cur_obs = self.env._get_obs()[0]
-        cur_heading = np.rad2deg(cur_obs['heading'])
-        # Make the action
-        new_obs = self.env.step(actions)[0]
-        new_heading = np.rad2deg(new_obs['heading'])
-        # Record the trajectory
-        self.traj[0]['path'].append(self.env.env.sims[0].gmap.bfs_shortest_path(cur_obs['viewpoint'], actions[0])[1:])
-        # Calculate the turned angle
-        turned_angle = new_heading - cur_heading
-        # Generate action description
-        cur_heading = angle_to_left_right(normalize_angle(cur_heading))
-        new_heading = angle_to_left_right(normalize_angle(new_heading))
-        action_description = f'Turn heading direction {turned_angle:.2f} degrees from {cur_heading} to {new_heading}.'
-        return action_description, new_obs
-
-    def rollout(self, reset=True):
-        if reset:  # Reset env
-            obs = self.env.reset()
-        else:
-            obs = self.env._get_obs()
-
-        global FINAL_STOP_POINT
-        global TEMP_STEPS_COUNTER
-
-        FINAL_STOP_POINT = obs[0]['stop']
-
-        if TEMP_STEPS_COUNTER != 0:
-            TEMP_STEPS_COUNTER = 0
-
-        print(obs[0].keys())
-        print(obs[0]['obs'])
-        print(obs[0]['obs_summary'])
-        print(obs[0]['objects'])
-        print(obs[0]['instr_id'])
-        print(obs[0]['scan'])
-        print(obs[0]['viewpoint'])
-        print(obs[0]['heading'])
-        print(obs[0]['elevation'])
-        print(obs[0]['candidate'])
-        print(obs[0]['instruction'])
-        print(obs[0]['gt_path'])
-        print(obs[0]['path_id'])
-        print(obs[0]['stop'])
-        print(obs[0]['start'])
-        print(obs[0]['target'])
-
-
-        print("==")
-
-        # Initialize the trajectory
-        self.init_trajecotry(obs)
-
-        for i, init_ob in enumerate(obs):
-            
-                navigable = init_ob['candidate']
-                heading = np.rad2deg(init_ob['heading'])
-                elevation = np.rad2deg(init_ob['elevation'])
-                orientation = f'\nheading: {heading:.2f}, elevation: {elevation:.2f}'
-
-            output = self.agent_executor(input)
-
-        return self.traj