More fixes to saving and reporting score

single-agent.py

@@ -1,4 +1,3 @@
-import random
 import torch as T
 import numpy as np
 import matplotlib.pyplot as plt
@@ -24,8 +23,8 @@ game = Game(n_players)
 agent = game.level.player_sprites[0].agent
 
 score_history = np.zeros(shape=(game.max_num_players, n_episodes))
-best_score = np.zeros(game.max_num_players)
-avg_score = np.zeros(game.max_num_players)
+best_score = 0
+avg_score = np.zeros(n_episodes)
 
 for i in tqdm(range(n_episodes)):
     # TODO: Make game.level.reset_map() so we don't __init__ everything all the time (such a waste)
@@ -55,22 +54,21 @@ for i in tqdm(range(n_episodes)):
     for player in game.level.player_sprites:
         exp_points = player.stats.exp
         score_history[player.player_id][i] = exp_points
-        avg_score[player.player_id] = np.mean(
-            score_history[player.player_id])
+        avg_score[i] = np.mean(score_history)
 
-    if np.mean(avg_score) > np.mean(best_score):
+    if avg_score[i] >= best_score:
         print(
-            f"\nNew Best score: {np.mean(avg_score)}\
-            \nOld Best score: {np.mean(best_score)}"
+            f"\nNew Best score: {avg_score[i]}\
+            \nOld Best score: {best_score}"
         )
-        best_score = avg_score
+        best_score = avg_score[i]
         print("Saving models for agent...")
         agent.save_models(
             actr_chkpt="player_actor", crtc_chkpt="player_critic")
         print("Models saved ...\n")
     else:
         print(
-            f"Average score of round: {np.mean(avg_score)}\
+            f"Average score of round: {avg_score[i]}\
               \nBest score: {np.mean(best_score)}"
         )
 
@@ -80,7 +78,7 @@ agent.save_models(
     actr_chkpt="player_actor", crtc_chkpt="player_critic")
 print("Models saved ...\n")
 
-plt.plot(score_history)
+plt.plot(avg_score)
 plt.savefig(figure_file)
 game.quit()