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ma09i038.py
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ma09i038.py
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from typing import List, Union
import numpy as np
from IPython.display import clear_output
import time
import os
import random
import traceback
BLACK = -1 #黒
WHITE = 1 #白
EMPTY = 0
def init_board(N:int=8):
# ボードを初期化 with an 8x8 numpy array
board = np.zeros((N, N), dtype=int)
# Set up the initial four stones
C0 = N//2
C1 = C0-1
board[C1, C1], board[C0, C0] = WHITE, WHITE # White
board[C1, C0], board[C0, C1] = BLACK, BLACK # Black
return board
def count_board(board, piece=EMPTY):
return np.sum(board == piece)
# Emoji representations for the pieces
BG_EMPTY = "\x1b[42m"
BG_RESET = "\x1b[0m"
# stone_codes = [
# f'黒',
# f'・',
# f'白',
# ]
stone_codes = [
f'{BG_EMPTY}⚫️{BG_RESET}',
f'{BG_EMPTY}🟩{BG_RESET}',
f'{BG_EMPTY}⚪️{BG_RESET}',
]
def stone(piece):
return stone_codes[piece+1]
def display_clear():
os.system('clear')
clear_output(wait=True)
BLACK_NAME=''
WHITE_NAME=''
def display_board(board, clear=True, sleep=0, black=None, white=None):
"""
オセロ盤を表示している.
"""
global BLACK_NAME, WHITE_NAME
if clear:
clear_output(wait=True)
if black:
BLACK_NAME=black
if white:
WHITE_NAME=white
for i, row in enumerate(board):
for piece in row:
print(stone(piece), end='')
if i == 1:
print(f' {BLACK_NAME}')
elif i == 2:
print(f' {stone(BLACK)}: {count_board(board, BLACK):2d}')
elif i == 3:
print(f' {WHITE_NAME}')
elif i == 4:
print(f' {stone(WHITE)}: {count_board(board, WHITE):2d}')
else:
print() # New line after each row
if sleep > 0:
time.sleep(sleep)
def all_positions(board):
N = len(board)
return [(r, c) for r in range(N) for c in range(N)]
# Directions to check (vertical, horizontal)
directions = [(0, 1), (1, 0), (0, -1), (-1, 0), (1, 1), (1, -1), (-1, -1), (-1, 1)]
def is_valid_move(board, row, col, player):
# Check if the position is within the board and empty
N = len(board)
if row < 0 or row >= N or col < 0 or col >= N or board[row, col] != 0:
return False
for dr, dc in directions:
r, c = row + dr, col + dc
if 0 <= r < N and 0 <= c < N and board[r, c] == -player:
while 0 <= r < N and 0 <= c < N and board[r, c] == -player:
r, c = r + dr, c + dc
if 0 <= r < N and 0 <= c < N and board[r, c] == player:
return True
return False
def get_valid_moves(board, player):
return [(r, c) for r, c in all_positions(board) if is_valid_move(board, r, c, player)]
def flip_stones(board, row, col, player):
N = len(board)
stones_to_flip = []
for dr, dc in directions:
directional_stones_to_flip = []
r, c = row + dr, col + dc
while 0 <= r < N and 0 <= c < N and board[r, c] == -player:
directional_stones_to_flip.append((r, c))
r, c = r + dr, c + dc
if 0 <= r < N and 0 <= c < N and board[r, c] == player:
stones_to_flip.extend(directional_stones_to_flip)
return stones_to_flip
def display_move(board, row, col, player):
stones_to_flip = flip_stones(board, row, col, player)
board[row, col] = player
display_board(board, sleep=0.3)
for r, c in stones_to_flip:
board[r, c] = player
display_board(board, sleep=0.1)
display_board(board, sleep=0.6)
def find_eagar_move(board, player):
valid_moves = get_valid_moves(board, player)
max_flips = 0
best_result = None
for r, c in valid_moves:
stones_to_flip = flip_stones(board, r, c, player)
if max_flips < len(stones_to_flip):
best_result = (r, c)
max_flips = len(stones_to_flip)
return best_result
class OthelloAI(object):
def __init__(self, face, name):
self.face = face
self.name = name
def __repr__(self):
return f"{self.face}{self.name}"
def move(self, board: np.array, piece: int)->tuple[int, int]:
valid_moves = get_valid_moves(board, piece)
return valid_moves[0]
def say(self, board: np.array, piece: int)->str:
if count_board(board, piece) >= count_board(board, -piece):
return 'やったー'
else:
return 'がーん'
class OchibiAI(OthelloAI):
def __init__(self, face, name, depth=6):
self.face = '🍑'
self.name = 'もも'
# def __init__(self, face, name):
# self.face = face
# self.name = name
def move(self, board: np.array, piece: int)->tuple[int, int]:
valid_moves = get_valid_moves(board, piece)
return valid_moves[0]
def board_play(player: OthelloAI, board, piece: int):
display_board(board, sleep=0)
if len(get_valid_moves(board, piece)) == 0:
print(f"{player}は、置けるところがありません。スキップします。")
return True
try:
start_time = time.time()
r, c = player.move(board.copy(), piece)
end_time = time.time()
except Exception as e:
print(f"{player.face}{player.name}は、エラーを発生させました。反則まけ")
print(traceback.format_exc())
return False
if not is_valid_move(board, r, c, piece):
print(f"{player}が返した({r},{c})には、置けません。反則負け。")
return False
display_move(board, r, c, piece)
return True
def comment(player1: OthelloAI, player2: OthelloAI, board):
try:
print(f"{player1}: {player1.say(board, BLACK)}")
except:
pass
try:
print(f"{player2}: {player2.say(board, WHITE)}")
except:
pass
def game(player1: OthelloAI, player2: OthelloAI,N=6):
board = init_board(N)
display_board(board, black=f'{player1}', white=f'{player2}')
while count_board(board, EMPTY) > 0:
if not board_play(player1, board, BLACK):
break
if not board_play(player2, board, WHITE):
break
comment(player1, player2, board)
# 危険エリア回避
class NamachaAI(OthelloAI):
def __init__(self):
self.face = '☕'
self.name = 'サブなまちゃまー'
#def __init__(self, face, name):
# self.face = face
# self.name = name
def move(self, board: np.array, piece: int)->tuple[int, int]:
best_moves = self.get_best_moves(board, piece)
return best_moves[0]
def get_yellow_area(self, N):
return [(0, 1), (0, N-2), (1, 0), (1, N-1), (N-2, 0), (N-2, N-1), (N-1, 1), (N-1, N-2)]
def get_red_area(self, N):
return [(1, 1), (1, N-2), (N-2, 1), (N-2, N-2)]
def get_best_moves(self, board, player, N=6):
#置ける場所を取得する
valid_moves = get_valid_moves(board, player)
#角に置かれる可能性があるエリアを除外
#参考(https://www.bodoge-intl.com/strategy/reverse/)
removed_danger_area = [piece for piece in valid_moves if piece not in self.get_red_area(N) and piece not in self.get_yellow_area(N)]
if removed_danger_area:
return removed_danger_area
else:
#レッドエリアのみ除外
removed_red_area = [piece for piece in valid_moves if piece not in self.get_red_area(N)]
if removed_red_area:
return removed_red_area
else:
return valid_moves
# ゲーム木・ミニマックス法
def display_move_no_display(board, row, col, player):
"""
ゲーム木のノード作成のために石を置いた後の盤面をシミュレートする
"""
stones_to_flip = flip_stones(board, row, col, player)
board[row, col] = player
#display_board(board, sleep=0.3)
for r, c in stones_to_flip:
board[r, c] = player
#display_board(board, sleep=0.1)
#display_board(board, sleep=0.6)
class GameTreeNode:
def __init__(self, board, player, move=None):
self.board = board
self.player = player
self.move = move
self.children = []
self.score = None
def create_children(self, depth):
"""
ゲーム木を再起呼び出しで作成する
"""
if depth == 0 or count_board(self.board, EMPTY) == 0:
self.score = evaluate_board(self.board)
return
for move in get_valid_moves(self.board, self.player):
new_board = self.board.copy()
display_move_no_display(new_board, *move, self.player)
child_node = GameTreeNode(new_board, -self.player, move)
self.children.append(child_node)
child_node.create_children(depth - 1)
def evaluate_board(board):
"""
ゲーム木のノードのスコアを算出する評価関数
"""
return count_board(board, BLACK) - count_board(board, WHITE)
def minimax(node, depth, maximizingPlayer, alpha=float('-inf'), beta=float('inf')):
"""
ミニマックスアルゴリズムでスコアを算出する
"""
if depth == 0 or node.children == []:
return evaluate_board(node.board)
if maximizingPlayer:
maxEval = float('-inf')
for child in node.children:
eval = minimax(child, depth-1, False, alpha, beta)
maxEval = max(maxEval, eval)
alpha = max(alpha, eval)
if beta <= alpha:
break
return maxEval
else:
minEval = float('inf')
for child in node.children:
eval = minimax(child, depth-1, True, alpha, beta)
minEval = min(minEval, eval)
beta = min(beta, eval)
if beta <= alpha:
break
return minEval
class NamachaAI2(OthelloAI):
def __init__(self, face, name, depth=6):
self.face = "🍵"
self.name = 'なまちゃまー'
# def __init__(self, face, name, depth=6):
# super().__init__(face, name)
# self.depth = depth
def move(self, board, piece):
# 現在の盤面で有効な手のリストを取得
valid_moves = get_valid_moves(board, piece)
# 有効な手がない場合はNoneを返す
if not valid_moves:
return None