Remove default model i will add back later, add back train.py, fix some rewarding

train.py

@@ -0,0 +1,30 @@
+from stable_baselines3 import PPO
+from utils.rl import SpaceInvadersEnv
+from stable_baselines3.common.vec_env import DummyVecEnv
+
+def make_env(rank: int, seed: int = 0):
+    def _init():
+        env = SpaceInvadersEnv()
+        return env
+    return _init
+
+env = SpaceInvadersEnv()
+
+n_envs = 128
+
+env = DummyVecEnv([make_env(i) for i in range(n_envs)])
+model = PPO(
+    "MlpPolicy", 
+    env, 
+    n_steps=8192,
+    batch_size=256,
+    n_epochs=7,
+    learning_rate=0.001,
+    verbose=1, 
+    device="cpu", 
+    gamma=0.985, 
+    ent_coef=0.015,
+    clip_range=0.2,
+)
+model.learn(75_000_000)
+model.save("invader_agent")

utils/constants.py

@@ -35,29 +35,29 @@ DIFFICULTY_SETTINGS = {
 
 DIFFICULTY_LEVELS = {
     "Easy": {
-        "enemy_rows": 3,
-        "enemy_cols": 4,
+        "enemy_rows": 2,
+        "enemy_cols": 3,
         "enemy_respawns": 5,
         "player_count": 2,
         "player_respawns": 2
     },
     "Medium": {
         "enemy_rows": 3,
-        "enemy_cols": 5,
+        "enemy_cols": 4,
         "enemy_respawns": 4,
         "player_count": 4,
         "player_respawns": 3
     },
     "Hard": {
         "enemy_rows": 4,
-        "enemy_cols": 6,
+        "enemy_cols": 5,
         "enemy_respawns": 3,
         "player_count": 6,
         "player_respawns": 4
     },
     "Extra Hard": {
-        "enemy_rows": 6,
-        "enemy_cols": 7,
+        "enemy_rows": 5,
+        "enemy_cols": 6,
         "enemy_respawns": 2,
         "player_count": 8,
         "player_respawns": 5

utils/rl.py

@@ -172,13 +172,13 @@ class SpaceInvadersEnv(gym.Env):
                     b = Bullet(self.player.center_x, self.player.center_y, 1)
                     self.bullets.append(b)
                 else:
-                    reward -= 0.05
+                    reward -= 0.02
 
             if self.enemy_formation.enemies:
                 nearest = self._nearest_enemy()
                 alignment = abs(nearest.center_x - self.player.center_x) / self.width
                 if alignment < 0.025:
-                    reward += 0.3
+                    reward += 0.1
 
             self.player.center_x = np.clip(self.player.center_x, 0, self.width)
             self.player_speed = (self.player.center_x - prev_x) / max(1e-6, PLAYER_SPEED)
@@ -222,7 +222,6 @@ class SpaceInvadersEnv(gym.Env):
                     if self.player_respawns_remaining > 0:
                         self.player_respawns_remaining -= 1
                         self._respawn_player()
-                        reward += 2.0 
                     else:
                         terminated = True
 
@@ -265,7 +264,7 @@ class SpaceInvadersEnv(gym.Env):
             if self.player.center_x < edge_threshold or self.player.center_x > self.width - edge_threshold:
                 reward -= 0.03
 
-        reward -= 0.005
+        reward -= 0.0025
 
         obs = self._obs()