Add comments and fix import errors

webots/controllers/RL_Supervisor/agent.py

@@ -160,7 +160,8 @@ def predict_action(self, state):
         probs = self.__neural_network.actor_network(state)
 
         if self.train_mode is True:
-            # Create a normal distribution with the calculated probabilities and the standard deviation
+            # Create a normal distribution with the calculated probabilities
+            # and the standard deviation
             dist = tfp.distributions.Normal(probs, self.__std_dev)
 
             # Sampling an action from the normal distribution
@@ -425,10 +426,17 @@ def learn(self, states, actions, old_probs, values, rewards, dones):
         # optimize Critic Network weights
         with tf.GradientTape() as tape:
 
+            #  The critical value represents the expected return from state 𝑠𝑡.
+            # It provides an estimate of how good it is to be in a given state.
             critic_value = self.__neural_network.critic_network(states)
-            returns = advantages + values
+
+            # the total discounted reward accumulated from time step 𝑡
+            estimate_returns = advantages + values
+
             # Generate loss
-            critic_loss = tf.math.reduce_mean(tf.math.pow(returns - critic_value, 2))
+            critic_loss = tf.math.reduce_mean(
+                tf.math.pow(estimate_returns - critic_value, 2)
+            )
 
         # calculate gradient
         critic_params = self.__neural_network.critic_network.trainable_variables

webots/controllers/RL_Supervisor/plotting.py

@@ -1,8 +1,8 @@
 """ Plotting script  with Matplotlib """
 
 # Imports
-import matplotlib.pyplot as plt
-import pandas as pd
+import matplotlib.pyplot as plt  # pylint: disable=import-error
+import pandas as pd  # pylint: disable=import-error
 
 # Define the path to the CSV file
 LOG_FILE = "logs/training_logs.csv"