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| from pwn import remote
import re
import math
import random
import time
ROWS = 6
COLUMNS = 7
WINDOW_LENGTH = 4
EMPTY = ''
PLAYER_PIECE = 'X'
AI_PIECE = 'O'
def parse_board(board_str):
lines = board_str.strip().split('\n')
board = []
for line in lines[-7:-1]:
row = line.strip('|').split('|')
row = [cell.strip() if cell.strip() != '' else EMPTY for cell in row]
board.append(row)
return board
def is_valid_location(board, col):
return board[0][col] == EMPTY
def get_next_open_row(board, col):
for row in range(ROWS-1, -1, -1):
if board[row][col] == EMPTY:
return row
return None
def drop_piece(board, row, col, piece):
board[row][col] = piece
def pop_piece(board, col):
for row in range(ROWS-1):
board[row+1][col] = board[row][col]
board[0][col] = EMPTY
def copy_board(board):
return [row[:] for row in board]
def winning_move(board, piece):
for c in range(COLUMNS - 3):
for r in range(ROWS):
if all(board[r][c+i] == piece for i in range(WINDOW_LENGTH)):
return True
for c in range(COLUMNS):
for r in range(ROWS - 3):
if all(board[r+i][c] == piece for i in range(WINDOW_LENGTH)):
return True
for c in range(COLUMNS - 3):
for r in range(ROWS - 3):
if all(board[r+i][c+i] == piece for i in range(WINDOW_LENGTH)):
return True
for c in range(COLUMNS - 3):
for r in range(WINDOW_LENGTH - 1, ROWS):
if all(board[r-i][c+i] == piece for i in range(WINDOW_LENGTH)):
return True
return False
def evaluate_window(window, piece):
score = 0
opp_piece = PLAYER_PIECE if piece == AI_PIECE else AI_PIECE
if window.count(piece) == 4:
score += 10000
elif window.count(piece) == 3 and window.count(EMPTY) == 1:
score += 100
elif window.count(piece) == 2 and window.count(EMPTY) == 2:
score += 10
if window.count(opp_piece) == 4:
score -= 10000
elif window.count(opp_piece) == 3 and window.count(EMPTY) == 1:
score -= 80
return score
def score_position(board, piece):
score = 0
position_score = [
[3, 4, 5, 7, 5, 4, 3],
[4, 6, 8,10, 8, 6, 4],
[5, 8,11,13,11, 8, 5],
[5, 8,11,13,11, 8, 5],
[4, 6, 8,10, 8, 6, 4],
[3, 4, 5, 7, 5, 4, 3],
]
for r in range(ROWS):
for c in range(COLUMNS):
if board[r][c] == piece:
score += position_score[r][c]
for r in range(ROWS):
row_array = [board[r][c] for c in range(COLUMNS)]
for c in range(COLUMNS - 3):
window = row_array[c:c+WINDOW_LENGTH]
score += evaluate_window(window, piece)
for c in range(COLUMNS):
col_array = [board[r][c] for r in range(ROWS)]
for r in range(ROWS - 3):
window = col_array[r:r+WINDOW_LENGTH]
score += evaluate_window(window, piece)
for r in range(ROWS - 3):
for c in range(COLUMNS - 3):
window = [board[r+i][c+i] for i in range(WINDOW_LENGTH)]
score += evaluate_window(window, piece)
for r in range(3, ROWS):
for c in range(COLUMNS - 3):
window = [board[r-i][c+i] for i in range(WINDOW_LENGTH)]
score += evaluate_window(window, piece)
return score
def get_valid_locations(board):
valid_locations = []
for c in range(COLUMNS):
if is_valid_location(board, c):
valid_locations.append(('d', c))
if board[ROWS-1][c] == AI_PIECE:
valid_locations.append(('p', c))
return valid_locations
def is_terminal_node(board):
return winning_move(board, PLAYER_PIECE) or winning_move(board, AI_PIECE) or len(get_valid_locations(board)) == 0
def minimax(board, depth, alpha, beta, maximizingPlayer, start_time, time_limit):
if time.time() - start_time > time_limit:
return (None, score_position(board, AI_PIECE))
valid_locations = get_valid_locations(board)
is_terminal = is_terminal_node(board)
if depth == 0 or is_terminal:
if is_terminal:
if winning_move(board, AI_PIECE):
return (None, float('inf'))
elif winning_move(board, PLAYER_PIECE):
return (None, float('-inf'))
else:
return (None, 0)
else:
return (None, score_position(board, AI_PIECE))
if maximizingPlayer:
value = float('-inf')
best_move = random.choice(valid_locations)
for action, col in valid_locations:
b_copy = copy_board(board)
if action == 'd':
row = get_next_open_row(b_copy, col)
drop_piece(b_copy, row, col, AI_PIECE)
elif action == 'p':
pop_piece(b_copy, col)
new_score = minimax(b_copy, depth-1, alpha, beta, False, start_time, time_limit)[1]
if new_score > value:
value = new_score
best_move = (action, col)
alpha = max(alpha, value)
if alpha >= beta:
break
if time.time() - start_time > time_limit:
break
return best_move, value
else:
value = float('inf')
best_move = random.choice(valid_locations)
for action, col in valid_locations:
b_copy = copy_board(board)
if action == 'd':
row = get_next_open_row(b_copy, col)
drop_piece(b_copy, row, col, PLAYER_PIECE)
elif action == 'p':
pop_piece(b_copy, col)
new_score = minimax(b_copy, depth-1, alpha, beta, True, start_time, time_limit)[1]
if new_score < value:
value = new_score
best_move = (action, col)
beta = min(beta, value)
if alpha >= beta:
break
if time.time() - start_time > time_limit:
break
return best_move, value
def find_best_move(board):
start_time = time.time()
time_limit = 1.8
best_move = ('d', random.choice(range(COLUMNS)))
best_score = float('-inf')
depth = 1
while True:
if time.time() - start_time > time_limit:
break
move, minimax_score = minimax(board, depth, float('-inf'), float('inf'), True, start_time, time_limit)
if time.time() - start_time > time_limit:
break
if minimax_score > best_score:
best_score = minimax_score
best_move = move
depth += 1
if depth > 6:
break
action, col = best_move
if action == 'd' and is_valid_location(board, col):
return action, col + 1
elif action == 'p':
return action, col + 1
else:
for c in range(COLUMNS):
if is_valid_location(board, c):
return 'd', c + 1
return 'd', 1
def main():
host = '0.cloud.chals.io'
port = 30265
conn = remote(host, port)
conn.recvuntil(b'Play in practice mode? [y/N]')
conn.sendline(b'n')
while True:
try:
output = conn.recvuntil([b'Do you want to drop or pop a piece? [d/p]', b'You win!', b'You lost', b'You lost the match.', b'Game'], timeout=10).decode()
print(output)
if 'You win!' in output or 'You lost!' in output or 'You lost the match.' in output:
if 'Game' in output:
continue
else:
break
if 'Game' in output and 'of 3' in output:
continue
board_match = re.search(r'Board:\n((?:.*\n){7})', output)
if board_match:
board_str = board_match.group(1)
board = parse_board(board_str)
action, column = find_best_move(board)
conn.sendline(action.encode())
conn.recvuntil(b'Which column? [1-7]')
conn.sendline(str(column).encode())
else:
pass
except EOFError:
print("Connection closed by the server.")
break
except Exception as e:
print(f"An error occurred: {e}")
break
try:
final_output = conn.recvall(timeout=5).decode()
print(final_output)
except EOFError:
pass
conn.close()
if __name__ == '__main__':
main()
|