fix call to learn in main

Author: philtabor

ReinforcementLearning/PolicyGradient/actor_critic/tensorflow2/main.py

@@ -18,7 +18,7 @@
 
     best_score = env.reward_range[0]
     score_history = []
-    load_checkpoint = False 
+    load_checkpoint = False
 
     if load_checkpoint:
         agent.load_models()
@@ -32,7 +32,7 @@
             observation_, reward, done, info = env.step(action)
             score += reward
             if not load_checkpoint:
-                agent.learn(observation, action, reward, observation_, done)
+                agent.learn(observation, reward, observation_, done)
             observation = observation_
         score_history.append(score)
         avg_score = np.mean(score_history[-100:])
@@ -47,4 +47,3 @@
     if not load_checkpoint:
         x = [i+1 for i in range(n_games)]
         plot_learning_curve(x, score_history, figure_file)
-