games.py

"""Games, or Adversarial Search (Chapter 5)"""

from collections import namedtuple
import random

from utils import argmax
from canvas import Canvas

infinity = float('inf')
GameState = namedtuple('GameState', 'to_move, utility, board, moves')

# ______________________________________________________________________________
# Minimax Search


def minimax_decision(state, game):
    """Given a state in a game, calculate the best move by searching
    forward all the way to the terminal states. [Figure 5.3]"""

    player = game.to_move(state)

    def max_value(state):
        if game.terminal_test(state):
            return game.utility(state, player)
        v = -infinity
        for a in game.actions(state):
            v = max(v, min_value(game.result(state, a)))
        return v

    def min_value(state):
        if game.terminal_test(state):
            return game.utility(state, player)
        v = infinity
        for a in game.actions(state):
            v = min(v, max_value(game.result(state, a)))
        return v

    # Body of minimax_decision:
    return argmax(game.actions(state),
                  key=lambda a: min_value(game.result(state, a)))

# ______________________________________________________________________________


def alphabeta_search(state, game):
    """Search game to determine best action; use alpha-beta pruning.
    As in [Figure 5.7], this version searches all the way to the leaves."""

    player = game.to_move(state)

    # Functions used by alphabeta
    def max_value(state, alpha, beta):
        if game.terminal_test(state):
            return game.utility(state, player)
        v = -infinity
        for a in game.actions(state):
            v = max(v, min_value(game.result(state, a), alpha, beta))
            if v >= beta:
                return v
            alpha = max(alpha, v)
        return v

    def min_value(state, alpha, beta):
        if game.terminal_test(state):
            return game.utility(state, player)
        v = infinity
        for a in game.actions(state):
            v = min(v, max_value(game.result(state, a), alpha, beta))
            if v <= alpha:
                return v
            beta = min(beta, v)
        return v

    # Body of alphabeta_cutoff_search:
    best_score = -infinity
    beta = infinity
    best_action = None
    for a in game.actions(state):
        v = min_value(game.result(state, a), best_score, beta)
        if v > best_score:
            best_score = v
            best_action = a
    return best_action


def alphabeta_cutoff_search(state, game, d=4, cutoff_test=None, eval_fn=None):
    """Search game to determine best action; use alpha-beta pruning.
    This version cuts off search and uses an evaluation function."""

    player = game.to_move(state)

    # Functions used by alphabeta
    def max_value(state, alpha, beta, depth):
        if cutoff_test(state, depth):
            return eval_fn(state)
        v = -infinity
        for a in game.actions(state):
            v = max(v, min_value(game.result(state, a),
                                 alpha, beta, depth + 1))
            if v >= beta:
                return v
            alpha = max(alpha, v)
        return v

    def min_value(state, alpha, beta, depth):
        if cutoff_test(state, depth):
            return eval_fn(state)
        v = infinity
        for a in game.actions(state):
            v = min(v, max_value(game.result(state, a),
                                 alpha, beta, depth + 1))
            if v <= alpha:
                return v
            beta = min(beta, v)
        return v

    # Body of alphabeta_cutoff_search starts here:
    # The default test cuts off at depth d or at a terminal state
    cutoff_test = (cutoff_test or
                   (lambda state, depth: depth > d or
                    game.terminal_test(state)))
    eval_fn = eval_fn or (lambda state: game.utility(state, player))
    best_score = -infinity
    beta = infinity
    best_action = None
    for a in game.actions(state):
        v = min_value(game.result(state, a), best_score, beta, 1)
        if v > best_score:
            best_score = v
            best_action = a
    return best_action

# ______________________________________________________________________________
# Players for Games


def query_player(game, state):
    """Make a move by querying standard input."""
    print("current state:")
    game.display(state)
    print("available moves: {}".format(game.actions(state)))
    print("")
    move_string = input('Your move? ')
    try:
        move = eval(move_string)
    except NameError:
        move = move_string
    return move


def random_player(game, state):
    """A player that chooses a legal move at random."""
    return random.choice(game.actions(state))


def alphabeta_player(game, state):
    return alphabeta_search(state, game)


# ______________________________________________________________________________
# Some Sample Games


class Game:
    """A game is similar to a problem, but it has a utility for each
    state and a terminal test instead of a path cost and a goal
    test. To create a game, subclass this class and implement actions,
    result, utility, and terminal_test. You may override display and
    successors or you can inherit their default methods. You will also
    need to set the .initial attribute to the initial state; this can
    be done in the constructor."""

    def actions(self, state):
        """Return a list of the allowable moves at this point."""
        raise NotImplementedError

    def result(self, state, move):
        """Return the state that results from making a move from a state."""
        raise NotImplementedError

    def utility(self, state, player):
        """Return the value of this final state to player."""
        raise NotImplementedError

    def terminal_test(self, state):
        """Return True if this is a final state for the game."""
        return not self.actions(state)

    def to_move(self, state):
        """Return the player whose move it is in this state."""
        return state.to_move

    def display(self, state):
        """Print or otherwise display the state."""
        print(state)

    def __repr__(self):
        return '<{}>'.format(self.__class__.__name__)

    def play_game(self, *players):
        """Play an n-person, move-alternating game."""
        state = self.initial
        while True:
            for player in players:
                move = player(self, state)
                state = self.result(state, move)
                if self.terminal_test(state):
                    self.display(state)
                    return self.utility(state, self.to_move(self.initial))


class Fig52Game(Game):
    """The game represented in [Figure 5.2]. Serves as a simple test case."""

    succs = dict(A=dict(a1='B', a2='C', a3='D'),
                 B=dict(b1='B1', b2='B2', b3='B3'),
                 C=dict(c1='C1', c2='C2', c3='C3'),
                 D=dict(d1='D1', d2='D2', d3='D3'))
    utils = dict(B1=3, B2=12, B3=8, C1=2, C2=4, C3=6, D1=14, D2=5, D3=2)
    initial = 'A'

    def actions(self, state):
        return list(self.succs.get(state, {}).keys())

    def result(self, state, move):
        return self.succs[state][move]

    def utility(self, state, player):
        if player == 'MAX':
            return self.utils[state]
        else:
            return -self.utils[state]

    def terminal_test(self, state):
        return state not in ('A', 'B', 'C', 'D')

    def to_move(self, state):
        return 'MIN' if state in 'BCD' else 'MAX'


class TicTacToe(Game):
    """Play TicTacToe on an h x v board, with Max (first player) playing 'X'.
    A state has the player to move, a cached utility, a list of moves in
    the form of a list of (x, y) positions, and a board, in the form of
    a dict of {(x, y): Player} entries, where Player is 'X' or 'O'."""

    def __init__(self, h=3, v=3, k=3):
        self.h = h
        self.v = v
        self.k = k
        moves = [(x, y) for x in range(1, h + 1)
                 for y in range(1, v + 1)]
        self.initial = GameState(to_move='X', utility=0, board={}, moves=moves)

    def actions(self, state):
        """Legal moves are any square not yet taken."""
        return state.moves

    def result(self, state, move):
        if move not in state.moves:
            return GameState(to_move=('O' if state.to_move == 'X' else 'X'),
                             utility=self.compute_utility(state.board, move, state.to_move),
                             board=state.board, moves=state.moves)  # Illegal move has no effect
        board = state.board.copy()
        board[move] = state.to_move
        moves = list(state.moves)
        moves.remove(move)
        return GameState(to_move=('O' if state.to_move == 'X' else 'X'),
                         utility=self.compute_utility(board, move, state.to_move),
                         board=board, moves=moves)

    def utility(self, state, player):
        """Return the value to player; 1 for win, -1 for loss, 0 otherwise."""
        return state.utility if player == 'X' else -state.utility

    def terminal_test(self, state):
        """A state is terminal if it is won or there are no empty squares."""
        return state.utility != 0 or len(state.moves) == 0

    def display(self, state):
        board = state.board
        for x in range(1, self.h + 1):
            for y in range(1, self.v + 1):
                print(board.get((x, y), '.'), end=' ')
            print()

    def compute_utility(self, board, move, player):
        """If 'X' wins with this move, return 1; if 'O' wins return -1; else return 0."""
        if (self.k_in_row(board, move, player, (0, 1)) or
                self.k_in_row(board, move, player, (1, 0)) or
                self.k_in_row(board, move, player, (1, -1)) or
                self.k_in_row(board, move, player, (1, 1))):
            return +1 if player == 'X' else -1
        else:
            return 0

    def k_in_row(self, board, move, player, delta_x_y):
        """Return true if there is a line through move on board for player."""
        (delta_x, delta_y) = delta_x_y
        x, y = move
        n = 0  # n is number of moves in row
        while board.get((x, y)) == player:
            n += 1
            x, y = x + delta_x, y + delta_y
        x, y = move
        while board.get((x, y)) == player:
            n += 1
            x, y = x - delta_x, y - delta_y
        n -= 1  # Because we counted move itself twice
        return n >= self.k


class ConnectFour(TicTacToe):
    """A TicTacToe-like game in which you can only make a move on the bottom
    row, or in a square directly above an occupied square.  Traditionally
    played on a 7x6 board and requiring 4 in a row."""

    def __init__(self, h=7, v=6, k=4):
        TicTacToe.__init__(self, h, v, k)

    def actions(self, state):
        return [(x, y) for (x, y) in state.moves
                if y == 1 or (x, y - 1) in state.board]


class Canvas_TicTacToe(Canvas):
    """Play a 3x3 TicTacToe game on HTML canvas
    TODO: Add restart button
    """
    def __init__(self, varname, player_1='human', player_2='random', id=None,
                 width=300, height=300):
        valid_players = ('human', 'random', 'alphabeta')
        if player_1 not in valid_players or player_2 not in valid_players:
            raise TypeError("Players must be one of {}".format(valid_players))
        Canvas.__init__(self, varname, id, width, height)
        self.ttt = TicTacToe()
        self.state = self.ttt.initial
        self.turn = 0
        self.strokeWidth(5)
        self.players = (player_1, player_2)
        self.draw_board()
        self.font("Ariel 30px")

    def mouse_click(self, x, y):
        player = self.players[self.turn]
        if self.ttt.terminal_test(self.state):
            return

        if player == 'human':
            x, y = int(3*x/self.width) + 1, int(3*y/self.height) + 1
            if (x, y) not in self.ttt.actions(self.state):
                # Invalid move
                return
            move = (x, y)
        elif player == 'alphabeta':
            move = alphabeta_player(self.ttt, self.state)
        else:
            move = random_player(self.ttt, self.state)
        self.state = self.ttt.result(self.state, move)
        self.turn ^= 1
        self.draw_board()

    def draw_board(self):
        self.clear()
        self.stroke(0, 0, 0)
        offset = 1/20
        self.line_n(0 + offset, 1/3, 1 - offset, 1/3)
        self.line_n(0 + offset, 2/3, 1 - offset, 2/3)
        self.line_n(1/3, 0 + offset, 1/3, 1 - offset)
        self.line_n(2/3, 0 + offset, 2/3, 1 - offset)
        board = self.state.board
        for mark in board:
            if board[mark] == 'X':
                self.draw_x(mark)
            elif board[mark] == 'O':
                self.draw_o(mark)
        if self.ttt.terminal_test(self.state):
            # End game message
            utility = self.ttt.utility(self.state, self.ttt.to_move(self.ttt.initial))
            if utility == 0:
                self.text_n('Game Draw!', 0.1, 0.1)
            else:
                self.text_n('Player {} wins!'.format(1 if utility > 0 else 2), 0.1, 0.1)
        else:  # Print which player's turn it is
            self.text_n("Player {}'s move({})".format(self.turn+1, self.players[self.turn]),
                        0.1, 0.1)

        self.update()

    def draw_x(self, position):
        self.stroke(0, 255, 0)
        x, y = [i-1 for i in position]
        offset = 1/15
        self.line_n(x/3 + offset, y/3 + offset, x/3 + 1/3 - offset, y/3 + 1/3 - offset)
        self.line_n(x/3 + 1/3 - offset, y/3 + offset, x/3 + offset, y/3 + 1/3 - offset)

    def draw_o(self, position):
        self.stroke(255, 0, 0)
        x, y = [i-1 for i in position]
        self.arc_n(x/3 + 1/6, y/3 + 1/6, 1/9, 0, 360)