diff --git a/src/active_bo_ros/active_bo_ros/interactive_bo_robot.py b/src/active_bo_ros/active_bo_ros/interactive_bo_robot.py
index 8b778b7..a248e8d 100644
--- a/src/active_bo_ros/active_bo_ros/interactive_bo_robot.py
+++ b/src/active_bo_ros/active_bo_ros/interactive_bo_robot.py
@@ -4,7 +4,6 @@ from active_bo_msgs.msg import ActiveBOResponse
 from active_bo_msgs.msg import ActiveRLRequest
 from active_bo_msgs.msg import ActiveRLResponse
 from active_bo_msgs.msg import ActiveBOState
-from active_bo_msgs.msg import DMP
 
 import rclpy
 from rclpy.node import Node
@@ -60,7 +59,7 @@ class ActiveBOTopic(Node):
         self.save_result = False
 
         # Active Reinforcement Learning Publisher, Subscriber and Message attributes
-        self.active_rl_pub = self.create_publisher(DMP,
+        self.active_rl_pub = self.create_publisher(ActiveRLRequest,
                                                    'active_rl_request',
                                                    1, callback_group=rl_callback_group)
         self.active_rl_sub = self.create_subscription(ActiveRLResponse,
@@ -143,7 +142,7 @@ class ActiveBOTopic(Node):
             self.overwrite = msg.overwrite
 
             # initialize
-            self.reward = np.ones((self.bo_runs, self.bo_episodes + self.nr_init - 1)) * -self.bo_steps
+            self.reward = np.ones((self.bo_runs, self.bo_episodes + self.nr_init - 1)) * -200
             self.best_pol_reward = np.ones((self.bo_runs, 1)) * -self.bo_steps
             self.best_policy = np.zeros((self.bo_runs, self.bo_steps, self.bo_nr_dims))
             self.best_weights = np.zeros((self.bo_runs, self.bo_nr_weights, self.bo_nr_dims))
@@ -204,25 +203,18 @@ class ActiveBOTopic(Node):
 
                 self.BO.reset_bo()
 
-                # self.BO.initialize()
                 self.init_pending = True
                 self.get_logger().info('BO Initialization is starting!')
-                # self.get_logger().info(f'{self.rl_pending}')
 
             if self.init_pending:
-                if self.bo_fixed_seed:
-                    seed = self.seed
-                else:
-                    seed = int(np.random.randint(1, 2147483647, 1)[0])
 
-                w = self.BO.policy_model.random_weights()
-
-                rl_msg = DMP()
+                rl_msg = ActiveRLRequest()
                 rl_msg.interactive_run = 2
-                rl_msg.p_x = w[:, 0]
-                rl_msg.p_y = w[:, 1]
+                rl_msg.weights = self.BO.policy_model.random_weights().flatten('F').tolist()
+                rl_msg.policy = self.BO.policy_model.rollout().flatten('F').tolist()
+                rl_msg.nr_weights = self.bo_nr_weights
                 rl_msg.nr_steps = self.bo_steps
-                rl_msg.nr_bfs = self.bo_nr_weights
+                rl_msg.nr_dims = self.bo_nr_dims
 
                 self.active_rl_pub.publish(rl_msg)
 
@@ -271,16 +263,13 @@ class ActiveBOTopic(Node):
 
                     np.savetxt(path, data, delimiter=',')
 
-
-
-                w = self.best_weights[best_policy_idx, :, :]
-
-                rl_msg = DMP()
+                rl_msg = ActiveRLRequest()
                 rl_msg.interactive_run = 1
-                rl_msg.p_x = w[:, 0]
-                rl_msg.p_y = w[:, 1]
+                rl_msg.weights = self.BO.policy_model.random_weights().flatten('F').tolist()
+                rl_msg.policy = self.BO.policy_model.rollout().flatten('F').tolist()
+                rl_msg.nr_weights = self.bo_nr_weights
                 rl_msg.nr_steps = self.bo_steps
-                rl_msg.nr_bfs = self.bo_nr_weights
+                rl_msg.nr_dims = self.bo_nr_dims
 
                 self.active_rl_pub.publish(rl_msg)
 
@@ -328,14 +317,13 @@ class ActiveBOTopic(Node):
 
                             self.BO.policy_model.set_weights(old_weights)
 
-                            w = self.BO.policy_model.weights
-
-                            rl_msg = DMP()
+                            rl_msg = ActiveRLRequest()
                             rl_msg.interactive_run = 0
-                            rl_msg.p_x = w[:, 0]
-                            rl_msg.p_y = w[:, 1]
+                            rl_msg.weights = self.BO.policy_model.random_weights().flatten('F').tolist()
+                            rl_msg.policy = self.BO.policy_model.rollout().flatten('F').tolist()
+                            rl_msg.nr_weights = self.bo_nr_weights
                             rl_msg.nr_steps = self.bo_steps
-                            rl_msg.nr_bfs = self.bo_nr_weights
+                            rl_msg.nr_dims = self.bo_nr_dims
 
                             self.active_rl_pub.publish(rl_msg)
 
@@ -348,14 +336,13 @@ class ActiveBOTopic(Node):
                             x_next = self.BO.next_observation()
                             self.BO.policy_model.set_weights(np.around(x_next, decimals=8))
 
-                            w = self.BO.policy_model.weights
-
-                            rl_msg = DMP()
+                            rl_msg = ActiveRLRequest()
                             rl_msg.interactive_run = 1
-                            rl_msg.p_x = w[:, 0]
-                            rl_msg.p_y = w[:, 1]
+                            rl_msg.weights = self.BO.policy_model.random_weights().flatten('F').tolist()
+                            rl_msg.policy = self.BO.policy_model.rollout().flatten('F').tolist()
+                            rl_msg.nr_weights = self.bo_nr_weights
                             rl_msg.nr_steps = self.bo_steps
-                            rl_msg.nr_bfs = self.bo_nr_weights
+                            rl_msg.nr_dims = self.bo_nr_dims
 
                             self.active_rl_pub.publish(rl_msg)