Esempio n. 1
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    def prior_knowledge_cmd(self, args):
        '''
        '''
        # get moves and probs for legal moves using function given in GoBoardUtilGo4, but with pass move
        moves, probs = GoBoardUtilGo4.generate_moves_with_feature_based_probs(
            self.board)
        priorKnowledgeList = GoBoardUtilGo4.prior_knowledge_initialization(
            moves, probs)
        color = self.board.current_player
        response = ""

        # convert moves from format 9 to a1
        for move in priorKnowledgeList:
            # jank? need to print PASS as Pass
            if move[0] == 'PASS':
                move[0] = 'Pass'
            else:
                move[0] = GoBoardUtil.format_point(
                    self.board._point_to_coord(move[0]))

        # sort by winrate, breaking ties alphabetically
        sortedList = sorted(priorKnowledgeList, key=lambda x: x[0])
        sortedList = sorted(sortedList, key=lambda x: x[3], reverse=True)
        for move in sortedList:
            response += move[0] + ' ' + str(int(
                (round(move[1])))) + ' ' + str(int(round((move[2])))) + ' '
        self.respond(response)
Esempio n. 2
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 def simulate(self, board, cboard, move, toplay):
     GoBoardUtilGo4.copyb2b(board, cboard)
     assert cboard.board.all() == board.board.all()
     cboard.move(move, toplay)
     opp = GoBoardUtilGo4.opponent(toplay)
     return GoBoardUtilGo4.playGame(cboard,
                                    opp,
                                    komi=self.komi,
                                    limit=self.limit,
                                    simulation_policy=simulations,
                                    use_pattern=self.use_pattern,
                                    check_selfatari=self.check_selfatari)
Esempio n. 3
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    def prior_knowledge_stat(self, board, root, color):
        s_color = GoBoardUtilGo4.int_to_color(color)

        stats = []
        for move, node in root._children.items():
            if color == BLACK:
                wins = node._black_wins
            else:
                wins = node._n_visits - node._black_wins
            visits = node._n_visits
            if visits:
                win_rate = round(float(wins) / visits, 2)
            else:
                win_rate = 0
            if move == PASS:
                move = None
            pointString = board.point_to_string(move)
            stats.append((pointString, wins, visits, win_rate))
        lst = sorted(stats, key=lambda i: i[3], reverse=True)
        master = []

        for stuff in lst:
            x = len(stuff) - 1
            # print(stuff[0:x])
            rnum = int(round(stuff[2]))

            # print(int(round(stuff[2])))
            lst1 = [stuff[0], stuff[1], rnum]
            master.append(lst1)

        #sys.stderr.write("Sstatistics: {} \n".format(lst))
        sys.stderr.flush()
        return master
Esempio n. 4
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 def print_stat(self, board, root, color):
     s_color = GoBoardUtilGo4.int_to_color(color)
     sys.stderr.write("Number of children {} \n".format(len(
         root._children)))
     sys.stderr.flush()
     sys.stderr.write("Number of roots visits: {} \n".format(
         root._n_visits))
     sys.stderr.flush()
     stats = []
     for move, node in root._children.items():
         if color == BLACK:
             wins = node._black_wins
         else:
             wins = node._n_visits - node._black_wins
         visits = node._n_visits
         if visits:
             win_rate = round(float(wins) / visits, 2)
         else:
             win_rate = 0
         if move == PASS:
             move = None
         pointString = board.point_to_string(move)
         stats.append((pointString, win_rate, wins, visits))
     sys.stderr.write("Statistics: {} \n".format(
         sorted(stats, key=lambda i: i[3], reverse=True)))
     sys.stderr.flush()
Esempio n. 5
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    def prior_knowledge_cmd(self,args):
        move, probs = self.probability(self.board)
        sim_probs = self.sim(probs, move, self.board)
        win_rate = self.winrates(probs, move, self.board)

        # print("winrates " + str(win_rate))
        wins = np.zeros(self.board.maxpoint)


        for num1 in range(len(move)):
            for num2 in range(0, len(move)-num1-1):
                if move[num2] != move[num2+1]:
                    if win_rate[move[num2]] < win_rate[move[num2+1]]:
                        move[num2], move[num2+1] = move[num2+1], move[num2]
                    elif win_rate[move[num2]]==win_rate[move[num2+1]]:
                        move1 = GoBoardUtilGo4.format_point(self.board._point_to_coord(move[num2]))
                        move2 = GoBoardUtilGo4.format_point(self.board._point_to_coord(move[num2+1]))

                        if(move1[0]>move2[0]):
                            move[num2] , move[num2+1] = move[num2+1] , move[num2]
        for elem in move:
            # print(GoBoardUtilGo4.format_point(self.board._point_to_coord(elem)), sim_probs[elem], win_rate[elem])
            wins[elem] = int(round(sim_probs[elem] * win_rate[elem]))
            # after calculating wins, we need to round simulation
            sim_probs[elem] = int(round(sim_probs[elem]))
            # wins[elem] = sim_probs[elem] * win_rate[elem]

        values = []

        for elem in move:
            # print(elem)
            elem2 = elem
            if elem == 0:
                elem2 = 'Pass'
                # print((elem2), sim_probs[elem], wins[elem])
                values.append(elem2)
                values.append(int(wins[elem]))
                values.append(int(sim_probs[elem]))

            else:
                # print(GoBoardUtilGo4.format_point(self.board._point_to_coord(elem2)), sim_probs[elem], wins[elem])
                values.append(GoBoardUtilGo4.format_point(self.board._point_to_coord(elem)))
                values.append(int(wins[elem]))
                values.append(int(sim_probs[elem]))

        str1 = ' '.join(str(e) for e in values)
        self.respond(''.join(str1))
Esempio n. 6
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    def good_print(self, board, node, color, num_nodes):
        cboard = board.copy()
        sys.stderr.write("\nTaking a tour of selection policy in tree! \n\n")
        sys.stderr.write(cboard.get_twoD_board())
        sys.stderr.flush()
        while not node.is_leaf():
            if node._move != None:
                if node._move != PASS:
                    pointString = board.point_to_string(move)
                else:
                    pointString = node._move
            else:
                pointString = 'Root'
            sys.stderr.write("\nMove: {} Numebr of children {}, Number of visits: {}\n"
                .format(pointString,len(node._children),node._n_visits))
            sys.stderr.flush()
            moves_ls = []
            max_flag = color == BLACK
            for move,child in node._children.items():
                uctval = uct_val(node,child,self.exploration,max_flag)
                moves_ls.append((move,uctval,child))
            moves_ls = sorted(moves_ls,key=lambda i:i[1],reverse=True)

            if moves_ls:
                sys.stderr.write("\nPrinting {} of {} childs that have highest UCT value \n\n".format(num_nodes, pointString))
                sys.stderr.flush()
                for i in range(num_nodes):
                    move = moves_ls[i][0]
                    child_val = moves_ls[i][1]
                    child_node = moves_ls[i][2]
                    if move !=PASS:
                        sys.stderr.write("\nChild point:{} ;UCT Value {}; Number of visits: {}; Number of Black wins: {}\n"
                            .format(cboard.point_to_string(move), child_val, child_node._n_visits, child_node._black_wins))
                        sys.stderr.flush()
                    else:
                        sys.stderr.write("\nChild point:{} ;UCT Value {}; Number of visits: {}; Number of Black wins: {} \n"
                            .format(move, child_val, child_node._n_visits, child_node._black_wins))
                        sys.stderr.flush()
            # Greedily select next move.
            max_flag = color == BLACK
            move, next_node = node.select(self.exploration,max_flag)
            if move==PASS:
                move = None
            assert cboard.check_legal(move, color)
            pointString = cboard.point_to_string(move)
            cboard.move(move, color)
            sys.stderr.write("\nBoard in simulation after chosing child {} in tree. \n".format(pointString))
            sys.stderr.write(cboard.get_twoD_board())
            sys.stderr.flush()
            color = GoBoardUtilGo4.opponent(color)
            node = next_node
        assert node.is_leaf()
        cboard.current_player = color
        leaf_value = self._evaluate_rollout(cboard, color)
        sys.stderr.write("\nWinner of simulation is: {} color, Black is 0 an \n".format(leaf_value))
        sys.stderr.flush()
Esempio n. 7
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 def update_with_move(self, last_move):
     """
     Step forward in the tree, keeping everything we already know about the subtree, assuming
     that get_move() has been called already. Siblings of the new root will be garbage-collected.
     """
     if last_move in self._root._children:
         self._root = self._root._children[last_move]
     else:
         self._root = TreeNode(None)
     self._root._parent = None
     self.toplay = GoBoardUtilGo4.opponent(self.toplay)
Esempio n. 8
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def writeMoves(board, moves, count, numSimulations):
    gtp_moves = []
    for i in range(len(moves)):
        if moves[i] != None:
            x, y = board._point_to_coord(moves[i])
            gtp_moves.append((GoBoardUtilGo4.format_point(
                (x, y)), float(count[i]) / float(numSimulations)))
        else:
            gtp_moves.append(('Pass', float(count[i]) / float(numSimulations)))
    sys.stderr.write("win rates: {}\n".format(
        sorted(gtp_moves, key=byPercentage, reverse=True)))
    sys.stderr.flush()
Esempio n. 9
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    def genmove_cmd(self, args):
        """
        generate a move for the specified color

        Arguments
        ---------
        args[0] : {'b','w'}
            the color to generate a move for
            it gets converted to  Black --> 1 White --> 2
            color : {0,1}
            board_color : {'b','w'}
        """
        try:
            board_color = args[0].lower()
            color = GoBoardUtilGo4.color_to_int(board_color)
            self.debug_msg("Board:\n{}\nko: {}\n".format(str(self.board.get_twoD_board()),
                                                          self.board.ko_constraint))
            move = self.go_engine.get_move(self.board, color)
            if move is None:
                self.respond("pass")
                return

            if not self.board.check_legal(move, color):
                move = self.board._point_to_coord(move)
                board_move = GoBoardUtilGo4.format_point(move)
                self.respond("Illegal move: {}".format(board_move))
                raise RuntimeError("Illegal move given by engine")

            # move is legal; play it
            self.board.move(move,color)

            self.debug_msg("Move: {}\nBoard: \n{}\n".format(move, str(self.board.get_twoD_board())))
            move = self.board._point_to_coord(move)
            board_move = GoBoardUtilGo4.format_point(move)
            self.respond(board_move)
        except Exception as e:
            self.respond('Error: {}'.format(str(e)))
            raise
Esempio n. 10
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    def _playout(self, board, color):
        """
        Run a single playout from the root to the given depth, getting a value at the leaf and
        propagating it back through its parents. State is modified in-place, so a copy must be
        provided.

        Arguments:
        board -- a copy of the board.
        color -- color to play
        

        Returns:
        None
        """
        node = self._root
        node._use_knowledge = self.in_tree_knowledge
        # This will be True only once for the root
        if not node._expanded:
            node.expand(board, color)
            
            #Avoid the division by zero errors
            if self.in_tree_knowledge == "probabilistic":
                b_wins_sum, n_visit_sum = 0,0
                for child in node._children.values():
                    b_wins_sum += child._black_wins
                    n_visit_sum += child._n_visits
                    
                node._black_wins = b_wins_sum
                node._n_visits = n_visit_sum
        while not node.is_leaf():
            # Greedily select next move.                
            max_flag = color == BLACK
            move, next_node = node.select(self.exploration,max_flag)
            if move!=PASS:
                assert board.check_legal(move, color)
            if move == PASS:
                move = None
            board.move(move, color)
            color = GoBoardUtilGo4.opponent(color) 
            node = next_node
        assert node.is_leaf()
        if not node._expanded:
            node.expand(board, color)

        assert board.current_player == color
        leaf_value = self._evaluate_rollout(board, color)  
        # Update value and visit count of nodes in this traversal.
        node.update_recursive(leaf_value)
Esempio n. 11
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 def _evaluate_rollout(self, board, toplay):
     """
     Use the rollout policy to play until the end of the game, returning +1 if the current
     player wins, -1 if the opponent wins, and 0 if it is a tie.
     """
     winner = GoBoardUtilGo4.playGame(board,
             toplay,
             komi=self.komi,
             limit=self.limit,
             simulation_policy=self.simulation_policy,
             use_pattern = self.use_pattern,
             check_selfatari= self.check_selfatari)
     if winner == BLACK:
         return 1
     else:
         return 0
Esempio n. 12
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    def prior_knowledge_cmd(self, args):
        """
        Return list of policy moves for the current_player of the board
        """
        policy_moves, _ = GoBoardUtilGo4.generate_all_policy_moves(
            self.board, self.go_engine.use_pattern,
            self.go_engine.check_selfatari)

        #policy_list.append("Pass")
        self.MCTS = MCTS()
        move_set = self.get_move(self.board, self.MCTS.toplay)
        #lst=self.MCTS.prior_knowledge_stat(self.board, self.MCTS._root, self.MCTS.toplay)
        move_string = ""
        for m_set in move_set:
            for m in m_set:
                move_string += str(m) + " "
        #print(move_string)
        move_stats = []
        self.respond("Statistics: " + str(move_string))
Esempio n. 13
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    def expandWithKnowledge(self, board, color):
        # how do i do initialize root values to be the sum of its children, need to do
        moves, probs = GoBoardUtilGo4.generate_moves_with_feature_based_probs(
            board)
        maxProb = max(probs)
        passProb = probs[-1]

        # move, wins, simulations
        priorKnowledgeList = []
        # populate priorKnowledgeList to check for moves and children
        for move in moves:
            # check for pass move
            if move == 'PASS':
                simulation = 10 * (passProb / maxProb)
                wins = (((passProb / maxProb) / 2) + 0.5) * simulation
                priorKnowledgeList.append([move, wins, simulation])
            # move is not pass
            else:
                simulation = 10 * (probs[move] / maxProb)
                wins = (((probs[move] / maxProb) / 2) + 0.5) * simulation
                priorKnowledgeList.append([move, wins, simulation])
        empty_points = board.get_empty_points()
        for move in empty_points:
            # move needs to be a legal one as well before init
            if move not in self._children and board.check_legal(
                    move, color) and not board.is_eye(move, color):
                self._children[move] = TreeNode(self)
                self._children[move]._move = move
                for point in priorKnowledgeList:
                    # need to replace 0's with values
                    if point[0] == move:
                        self._children[move]._black_wins = point[1]
                        self._children[move]._n_visits = point[2]

        self._children[PASS] = TreeNode(self)
        self._children[PASS]._move = PASS
        self._children[PASS]._black_wins = priorKnowledgeList[-1][1]
        self._children[PASS]._n_visits = priorKnowledgeList[-1][2]
        self._expanded = True
Esempio n. 14
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    def _playout(self, board, color):
        """
        Run a single playout from the root to the given depth, getting a value at the leaf and
        propagating it back through its parents. State is modified in-place, so a copy must be
        provided.

        Arguments:
        board -- a copy of the board.
        color -- color to play
        

        Returns:
        None
        """
        node = self._root
        # This will be True only once for the root
        if not node._expanded:
            node.expand(board, color)
        while not node.is_leaf():
            # Greedily select next move.
            max_flag = color == BLACK
            move, next_node = node.select(self.exploration, max_flag)
            if move != PASS:
                assert board.check_legal(move, color)
            if move == PASS:
                move = None
            board.move(move, color)
            color = GoBoardUtilGo4.opponent(color)
            node = next_node
        assert node.is_leaf()
        if not node._expanded:
            node.expand(board, color)

        assert board.current_player == color
        leaf_value = self._evaluate_rollout(board, color)
        # Update value and visit count of nodes in this traversal.
        node.update_recursive(leaf_value)