added ghost direction to state

ReinforcmentLearning/util.py

@@ -18,8 +18,24 @@ def initial_q_fill():
 
     for x in range(-7, 8):
         for y in range(-2, 3):
+            for ghost_direction in Direction:
+                for cookie_direction in Direction:
+                    state = (x, y, ghost_direction, cookie_direction)
+                    q_values[state] = np.zeros(4)
+
+                    for action_idx in range(len(Direction)):
+                        q_values[state][action_idx] = random.random() * 0.2 - 0.1
+
+    return q_values
+
+
+def initial_q_fill_only_surroundings():
+    q_values = {}
+
+    for ghost_distance in [1, 2]:
+        for ghost_direction in Direction:
             for cookie_direction in Direction:
-                state = (x, y, cookie_direction)
+                state = (ghost_distance, ghost_direction, cookie_direction)
                 q_values[state] = np.zeros(4)
 
                 for action_idx in range(len(Direction)):
@@ -28,14 +44,30 @@ def initial_q_fill():
     return q_values
 
 
-
 def calc_current_state(labyrinth, pac_x, pac_y, ghost_x, ghost_y):
     x_ghost_dist = pac_x - ghost_x
     y_ghost_dist = pac_y - ghost_y
 
     cookie_direction = get_closest_cookie_direction(labyrinth, pac_x, pac_y)
 
-    return x_ghost_dist, y_ghost_dist, cookie_direction
+    ghost_direction = cords_to_direction(x_ghost_dist, y_ghost_dist)
+
+    return x_ghost_dist, y_ghost_dist, ghost_direction, cookie_direction
+
+
+def calc_current_state_surroundings(labyrinth, pac_x, pac_y, ghost_x, ghost_y):
+    x_ghost_dist = abs(pac_x - ghost_x)
+    y_ghost_dist = abs(pac_y - ghost_y)
+
+    ghost_distance_sum = x_ghost_dist + y_ghost_dist
+    ghost_distance = 1 if ghost_distance_sum == 1 else 2
+
+    ghost_direction = cords_to_direction(x_ghost_dist, y_ghost_dist)
+
+    cookie_direction = get_closest_cookie_direction(labyrinth, pac_x, pac_y)
+
+    return ghost_distance, ghost_direction, cookie_direction
+
 
 
 def get_closest_cookie_direction(labyrinth, pac_x, pac_y):