The following code describes an AI TicTacToe game(the main file is game.py)
**player.py:**
import math
import random
class Player():
def __init__(self, letter):
self.letter = letter
def get_move(self, game):
pass
class HumanPlayer(Player):
def __init__(self, letter):
super().__init__(letter)
def get_move(self, game):
valid_square = False
val = None
while not valid_square:
square = input(self.letter + '\'s turn. Input move (0-9): ')
try:
val = int(square)
if val not in game.available_moves():
raise ValueError
valid_square = True
except ValueError:
print('Invalid square. Try again.')
return val
class RandomComputerPlayer(Player):
def __init__(self, letter):
super().__init__(letter)
def get_move(self, game):
square = random.choice(game.available_moves())
return square
class SmartComputerPlayer(Player):
def __init__(self, letter):
super().__init__(letter)
def get_move(self, game):
if len(game.available_moves()) == 9:
square = random.choice(game.available_moves())
else:
square = self.minimax(game, self.letter)['position']
return square
def minimax(self, state, player):
max_player = self.letter # yourself
other_player = 'O' if player == 'X' else 'X'
# first we want to check if the previous move is a winner
if state.current_winner == other_player:
return {'position': None, 'score': 1 * (state.num_empty_squares() + 1) if other_player == max_player else -1 * (
state.num_empty_squares() + 1)}
elif not state.empty_squares():
return {'position': None, 'score': 0}
if player == max_player:
best = {'position': None, 'score': -math.inf} # each score should maximize
else:
best = {'position': None, 'score': math.inf} # each score should minimize
for possible_move in state.available_moves():
state.make_move(possible_move, player)
sim_score = self.minimax(state, other_player) # simulate a game after making that move
# undo move
state.board[possible_move] = ' '
state.current_winner = None
sim_score['position'] = possible_move # this represents the move optimal next move
if player == max_player: # X is max player
if sim_score['score'] > best['score']:
best = sim_score
else:
if sim_score['score'] < best['score']:
best = sim_score
return best
**game.py:**
import math
import time
from player import HumanPlayer, RandomComputerPlayer, SmartComputerPlayer
class TicTacToe():
def __init__(self):
self.board = self.make_board()
self.current_winner = None
@staticmethod
def make_board():
return [' ' for _ in range(9)]
def print_board(self):
for row in [self.board[i*3:(i+1) * 3] for i in range(3)]:
print('| ' + ' | '.join(row) + ' |')
@staticmethod
def print_board_nums():
# 0 | 1 | 2
number_board = [[str(i) for i in range(j*3, (j+1)*3)] for j in range(3)]
for row in number_board:
print('| ' + ' | '.join(row) + ' |')
def make_move(self, square, letter):
if self.board[square] == ' ':
self.board[square] = letter
if self.winner(square, letter):
self.current_winner = letter
return True
return False
def winner(self, square, letter):
# check the row
row_ind = math.floor(square / 3)
row = self.board[row_ind*3:(row_ind+1)*3]
# print('row', row)
if all([s == letter for s in row]):
return True
col_ind = square % 3
column = [self.board[col_ind+i*3] for i in range(3)]
# print('col', column)
if all([s == letter for s in column]):
return True
if square % 2 == 0:
diagonal1 = [self.board[i] for i in [0, 4, 8]]
# print('diag1', diagonal1)
if all([s == letter for s in diagonal1]):
return True
diagonal2 = [self.board[i] for i in [2, 4, 6]]
# print('diag2', diagonal2)
if all([s == letter for s in diagonal2]):
return True
return False
def empty_squares(self):
return ' ' in self.board
def num_empty_squares(self):
return self.board.count(' ')
def available_moves(self):
return [i for i, x in enumerate(self.board) if x == " "]
def play(game, x_player, o_player, print_game=True):
if print_game:
game.print_board_nums()
letter = 'X'
while game.empty_squares():
if letter == 'O':
square = o_player.get_move(game)
else:
square = x_player.get_move(game)
if game.make_move(square, letter):
if print_game:
print(letter + ' makes a move to square {}'.format(square))
game.print_board()
print('')
if game.current_winner:
if print_game:
print(letter + ' wins!')
return letter # ends the loop and exits the game
letter = 'O' if letter == 'X' else 'X' # switches player
time.sleep(.8)
if print_game:
print('It\'s a tie!')
if __name__ == '__main__':
x_player = SmartComputerPlayer('X')
o_player = HumanPlayer('O')
t = TicTacToe()
play(t, x_player, o_player, print_game=True)
As you can see, the programmer used an minimx algorithmus to minimize the possibility to lose and to maximize the possibility to win. Now after several days of trying to understand how this minimax method works, I can't help but ask you guys to explain this to me.
1.what is the reasoning behind adding this code to player.py and how does the method return a score that will be greater than the initial value of negative infinity?:
if player == max_player:
best = {'position': None, 'score': -math.inf}
else:
best = {'position': None, 'score': math.inf}
2.in our simscore variabel we added the otherplayer parameters into our minimax function. Why did we do that? And doesnt we need to add the variable max_player as a parameter to minimax() to simulate a game?
3. How does recursion in this specific case work?
