Update marin002.py

marin002.py

@@ -217,20 +217,53 @@ def move(self, board, color: int)->tuple[int, int]:
         selected_move = random.choice(valid_moves)
         return selected_move
 
-### 自分の作ったAIをここに貼る
-
-import random
-
-class MosAI(OthelloAI):
-    def __init__(self, face, name):
+class IchigoAI(OthelloAI):
+    def __init__(self, face, name, depth=3):
         self.face = face
         self.name = name
+        self.depth = depth
 
     def move(self, board, color: int)->tuple[int, int]:
         """
         ボードが与えられたとき、どこに置くか(row,col)を返す
         """
+        _, move = self.minimax(board, color, self.depth, float('-inf'), float('inf'), True)
+        return move
+
+    def minimax(self, board, color, depth, alpha, beta, maximizing_player):
+        if depth == 0 or len(get_valid_moves(board, color)) == 0:
+            return self.evaluate(board, color), None
+
         valid_moves = get_valid_moves(board, color)
-        # ランダムに選ぶ
-        selected_move = random.choice(valid_moves)
-        return selected_move
+        if maximizing_player:
+            max_eval = float('-inf')
+            best_move = None
+            for move in valid_moves:
+                new_board = board.copy()
+                flip_stones(new_board, move[0], move[1], color)
+                eval, _ = self.minimax(new_board, -color, depth - 1, alpha, beta, False)
+                if eval > max_eval:
+                    max_eval = eval
+                    best_move = move
+                alpha = max(alpha, eval)
+                if beta <= alpha:
+                    break
+            return max_eval, best_move
+        else:
+            min_eval = float('inf')
+            best_move = None
+            for move in valid_moves:
+                new_board = board.copy()
+                flip_stones(new_board, move[0], move[1], color)
+                eval, _ = self.minimax(new_board, -color, depth - 1, alpha, beta, True)
+                if eval < min_eval:
+                    min_eval = eval
+                    best_move = move
+                beta = min(beta, eval)
+                if beta <= alpha:
+                    break
+            return min_eval, best_move
+
+    def evaluate(self, board, color):
+        # A simple evaluation function: the difference in the number of pieces.
+        return count_board(board, color) - count_board(board, -color)