diff --git a/scripts/MiniMaxAlgo/player.py b/scripts/MiniMaxAlgo/player.py index 2ffe8cc..34e997c 100644 --- a/scripts/MiniMaxAlgo/player.py +++ b/scripts/MiniMaxAlgo/player.py @@ -36,3 +36,46 @@ class RandomComputerPlayer(Player): 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