Доброго времени суток ,помогите пожалуйста с решением задачи ,кому не сложно . Вот критерии
Сделайте сетку 5 из 5.
Добавьте бриллиант в игру, узнав, какой игрок получает
дополнительные 500 баллов.
Добавить опцию стрельбы монстров, только с одним игроком
стрелка и если вы убьете монстра, вы получите 250 бонусных очков.
Поиск алмаза и стрельба в монстра должны быть описаны в
описание, которое появляется во время игры.
Если вам не сложно , для меня это очень важно. Заранее благодарю.
Сам код
%------------------------------------------------------------------------------
% A Prolog Implementation of the Wumpus World described in
% Artificial Intelligence : A Modern Approach (Russel - Norvig)
%
% Mandatory Excercise 2007
% v1.0 - Jan. 31, 2007
% Richard O. Legendi
%
% Copied into prolog-examples with permission Richard O. Legendi
% Original exercise descriped in Artificial Intelligence : A Modern Approach (Russel - Norvig)
%
% Usage:
% consult this file
% ?-start.
%
%------------------------------------------------------------------------------
%------------------------------------------------------------------------------
% Declaring dynamic methods
:- dynamic ([
agent_location/1,
gold_location/1,
pit_location/1,
time_taken/1,
score/1,
visited/1,
visited_cells/1,
world_size/1,
wumpus_location/1,
isPit/2,
isWumpus/2,
isGold/2
]).
%------------------------------------------------------------------------------
% To start the game
start :-
format('Initializing started...~n', []),
init,
format('Let the game begin!~n', []),
take_steps([[1,1]]).
%------------------------------------------------------------------------------
% Scheduling simulation:
step_pre(VisitedList) :-
agent_location(AL),
gold_location(GL),
wumpus_location(WL),
score(S),
time_taken(T),
( AL=GL -> writeln('WON!'), format('Score: ~p,~n Time: ~p', [S,T])
; AL=WL -> format('Lost: Wumpus eats you!~n', []),
format('Score: ~p,~n Time: ~p', [S,T])
; take_steps(VisitedList)
).
take_steps(VisitedList) :-
make_percept_sentence(Perception),
agent_location(AL),
format('I\'m in ~p, seeing: ~p~n', [AL,Perception]),
update_KB(Perception),
ask_KB(VisitedList, Action),
format('I\'m going to: ~p~n', [Action]),
update_time,
update_score,
agent_location(Aloc),
VL = [Aloc|VisitedList],
standing,
step_pre(VL).
%------------------------------------------------------------------------------
% Updating states
update_time :-
time_taken(T),
NewTime is T+1,
retractall( time_taken(_) ),
assert( time_taken(NewTime) ).
update_score :-
agent_location(AL),
gold_location(GL),
wumpus_location(WL),
update_score(AL, GL, WL).
update_score(P) :-
score(S),
NewScore is S+P,
retractall( score(_) ),
assert( score(NewScore) ).
update_score(AL, AL, _) :-
update_score(1000).
update_score(_,_,_) :-
update_score(-1).
update_agent_location(NewAL) :-
retractall( agent_location(_) ),
assert( agent_location(NewAL) ).
is_pit(no, X) :-
\+ pit_location(X).
is_pit(yes, X) :-
pit_location(X).
%------------------------------------------------------------------------------
% Display standings
standing :-
wumpus_location(WL),
gold_location(GL),
agent_location(AL),
( is_pit(yes, AL) -> format('Agent was fallen into a pit!~n', []),
fail
; stnd(AL, GL, WL)
%\+ pit_location(yes, Al),
).
stnd(_, _, _) :-
format('There\'s still something to do...~n', []).
stnd(AL, _, AL) :-
format('YIKES! You\'re eaten by the wumpus!', []),
fail.
stnd(AL, AL, _) :-
format('AGENT FOUND THE GOLD!!', []),
true.
%------------------------------------------------------------------------------
% Perceptotion
make_perception([_Stench,_Bleeze,_Glitter]) :-
agent_location(AL),
isStinky(AL),
isBleezie(AL),
isGlittering(AL).
test_perception :-
make_percept_sentence(Percept),
format('I feel ~p, ',[Percept]).
make_percept_sentence([Stench,Bleeze,Glitter]) :-
smelly(Stench),
bleezy(Bleeze),
glittering(Glitter).
%------------------------------------------------------------------------------
% Initializing
init :-
init_game,
init_land_fig72,
init_agent,
init_wumpus.
init_game :-
retractall( time_taken(_) ),
assert( time_taken(0) ),
retractall( score(_) ),
assert( score(0) ),
retractall( visited(_) ),
assert( visited(1) ),
retractall( isWumpus(_,_) ),
retractall( isGold(_,_) ),
retractall( visited_cells(_) ),
assert( visited_cells([]) ).
% To set the situation described in Russel-Norvig's book (2nd Ed.),
% according to Figure 7.2
init_land_fig72 :-
retractall( world_size(_) ),
assert( world_size(4) ),
retractall( gold_location(_) ),
assert( gold_location([3,2]) ),
retractall( pit_location(_) ),
assert( pit_location([4,4]) ),
assert( pit_location([3,3]) ),
assert( pit_location([1,3]) ).
init_agent :-
retractall( agent_location(_) ),
assert( agent_location([1,1]) ),
visit([1,1]).
init_wumpus :-
retractall( wumpus_location(_) ),
assert( wumpus_location([4,1]) ).
visit(Xs) :-
visited_cells(Ys),
retractall( visited_cells(_) ),
assert( visited_cells([Ys|Xs]) ).
%------------------------------------------------------------------------------
% Perceptors
%%% Institiation error!!!
%adj(X,Y) :-
% world_size(WS),
% ( X is Y+1, Y < WS
% ; X is Y-1, Y-1 > 0
% ).
adj(1,2).
adj(2,1).
adj(2,3).
adj(3,2).
adj(3,4).
adj(4,3).
adjacent( [X1, Y1], [X2, Y2] ) :-
( X1 = X2, adj( Y1, Y2 )
; Y1 = Y2, adj( X1, X2 )
).
%adjacent([X1,Y],[X2,Y]) :-
% adj(X1,X2).
%adjacent([X,Y1],[X,Y2]) :-
% adj(Y1,Y2).
isSmelly(Ls1) :-
wumpus_location( Ls2 ),
adjacent( Ls1, Ls2 ).
isBleezy(Ls1) :-
pit_location( Ls2 ),
adjacent( Ls1, Ls2 ).
isGlittering( [X1, Y1] ) :-
gold_location( [X2, Y2] ),
X1 = X2,
Y1 = Y2.
bleezy(yes) :-
agent_location(AL),
isBleezy(AL).
bleezy(no).
smelly(yes) :-
agent_location(AL),
isSmelly(AL).
smelly(no).
glittering(yes) :-
agent_location(AL),
isGlittering(AL).
glittering(no).
%------------------------------------------------------------------------------
% Knowledge Base:
update_KB( [Stench,Bleeze,Glitter] ) :-
add_wumpus_KB(Stench),
add_pit_KB(Bleeze),
add_gold_KB(Glitter).
% if it would be 'yes' -> it would mean the player is eaten ;]
add_wumpus_KB(no) :-
%agent_location(L1),
%adjacent(L1, L2),
%assume_wumpus(no, L2).
agent_location([X,Y]),
world_size(_),
% Checking needed!!
% adj will freeze for (4,_) !!
Z1 is Y+1, assume_wumpus(no,[X,Z1]),
Z2 is Y-1, assume_wumpus(no,[X,Z2]),
Z3 is X+1, assume_wumpus(no,[Z3,Y]),
Z4 is X-1, assume_wumpus(no,[Z4,Y]).
add_pit_KB(no) :-
agent_location([X,Y]),
Z1 is Y+1, assume_pit(no,[X,Z1]),
Z2 is Y-1, assume_pit(no,[X,Z2]),
Z3 is X+1, assume_pit(no,[Z3,Y]),
Z4 is X-1, assume_pit(no,[Z4,Y]).
% Checking needed!! If its not already in the KB !!!
add_pit_KB(yes) :-
agent_location([X,Y]),
Z1 is Y+1, assume_pit(yes,[X,Z1]),
Z2 is Y-1, assume_pit(yes,[X,Z2]),
Z3 is X+1, assume_pit(yes,[Z3,Y]),
Z4 is X-1, assume_pit(yes,[Z4,Y]).
add_gold_KB(no) :-
gold_location(GL),
assume_gold(no, GL).
add_gold_KB(yes) :-
gold_location([X1,Y1]),
agent_location([X2,Y2]),
X1 = X2, Y1 = Y2,
assume_gold(yes, [X1,Y1]).
assume_wumpus(no, L) :-
retractall( isWumpus(_, L) ),
assert( isWumpus(no, L) ),
format('KB learn ~p - no Wumpus there!~n', [L]).
assume_wumpus(yes, L) :-
%wumpus_healthy, % Will be included ...
retractall( isWumpus(_, L) ),
assert( isWumpus(yes, L) ),
format('KB learn ~p - possibly the Wumpus is there!~n', [L]).
assume_pit(no, L) :-
retractall( isPit(_, L) ),
assert( isPit(no, L) ),
format('KB learn ~p - there\'s no Pit there!~n', [L]).
assume_pit(yes, L) :-
retractall( isPit(_, L) ),
assert( isPit(yes, L) ),
format('KB learn ~p - its a Pit!~n', [L]).
assume_gold(no, L) :-
retractall( isGold(_, L) ),
assert( isGold(no, L) ),
format('KB learn ~p - there\'s no gold here!~n', [L]).
assume_gold(yes, L) :-
retractall( isGold(_, L) ),
assert( isGold(yes, L) ),
format('KB learn ~p - GOT THE GOLD!!!~n', [L]).
permitted([X,Y]) :-
world_size(WS),
0 < X, X < WS+1,
0 < Y, Y < WS+1.
ask_KB(VisitedList, Action) :-
isWumpus(no, L),
isPit(no, L),
permitted(L),
not_member(L, VisitedList),
update_agent_location(L),
Action = L.
%------------------------------------------------------------------------------
% Utils
not_member(_, []).
not_member([X,Y], [[U,V]|Ys]) :-
( X=U,Y=V -> fail
; not_member([X,Y], Ys)
).
