(self, game)
return self.d[game.ttentry()]["move"]
This method enables the transposition table to be used
        like an AI algorithm. However it will just break if it falls
        on some game state that is not in the table. Therefore it is a
        better option to use a mixed algorithm like

        >>> # negamax boosted with a transposition table !
        >>> Negamax(10, tt= my_dictTranspositionTable)
This method enables the transposition table to be used
        like an AI algorithm. However it will just break if it falls
        on some game state that is not in the table. Therefore it is a
        better option to use a mixed algorithm like
This method enables the transposition table to be used like an AI algorithm . However it will just break if it falls on some game state that is not in the table . Therefore it is a better option to use a mixed algorithm like
def __call__(self, game):
        """
        This method enables the transposition table to be used
        like an AI algorithm. However it will just break if it falls
        on some game state that is not in the table. Therefore it is a
        better option to use a mixed algorithm like

        >>> # negamax boosted with a transposition table !
        >>> Negamax(10, tt= my_dictTranspositionTable)
        """
        return self.d[game.ttentry()]["move"]
def __call__ ( self , game ) : return self . d [ game . ttentry ( ) ] [ "move" ]