Cel*_*ibi 6 prolog constraint-programming
在这里,我建议找到这里定义的 Smullyan数值机器的解决方案.
它们是将数字列表作为输入的机器,并根据输入模式将其转换为遵循某些规则的另一个数字列表.以下是上面链接中给出的机器规则,更正式地表达了一下.假设M是机器,M(X)是X的变换.我们定义了一些这样的规则:
M(2X) = X
M(3X) = M(X)2M(X)
M(4X) = reverse(M(X)) // reverse the order of the list.
M(5X) = M(X)M(X)
任何与任何规则都不匹配的内容都会被拒绝.这里有一些例子:
问题是,找到X这样:
这是第二个例子,与穷举搜索相比有点复杂(特别是如果我想要前10或100个解决方案).
M(1X2) = X
M(3X) = M(X)M(X)
M(4X) = reverse(M(X))
M(5X) = truncate(M(X)) // remove the first element of the list truncate(1234) = 234. Only valid if M(X) has at least 2 elements.
M(6X) = 1M(X)
M(7X) = 2M(X)
问题:
在Prolog中编写求解器非常简单.除了它只是详尽的探索(又名蛮力),可能需要一些时间来制定一些规则.
我试过但是无法用CLP(FD)的逻辑约束来表达这个问题,所以我尝试用CHR(约束处理规则)来表达对列表的约束(特别是append约束),但无论我如何表达它,它总是归结为详尽的搜索.
知道我可以采取什么方法在合理的时间内解决这类问题吗？理想情况下,我希望能够生成比某些绑定更短的所有解决方案.
让我们来看看你的"更复杂"的问题.详尽的搜索功能非常出色!
这是与Сергей的解决方案的比较,通过考虑共同的目标可以显着改善:
m([1|A], X) :-
A = [_|_],
append(X, [2], A).
m([E | X], Z) :-
m(X, Y),
( E = 3,
append(Y, Y, Z)
; E = 4,
reverse(Y, Z)
; E = 5,
Y = [_ | Z]
; E = 6,
Z = [1 | Y]
; E = 7,
Z = [2 | Y]
).
对于查询,time(findall(_, (question3(X), write(X), nl), _)).我得到B 8.1,SICStus 4.3b8:
??????? B tabled 104.542s
??????? B 678.394s
false B 16.013s
false B tabled 53.007s
??????? SICStus 439.210s
false SICStus 7.990s
??????? SWI 1383.678s, 5,363,110,835 inferences
false SWI 44.743s, 185,136,302 inferences
其他问题并不难回答.只有SICStus以上m/2和
call_nth/2:
| ?- time(call_nth( (
length(Xs0,N),append(Xs0,Xs0,Ys),m(Xs0,Ys),
writeq(Ys),nl ), 10)).
[4,3,7,4,3,1,4,3,7,4,3,1,2,4,3,7,4,3,1,4,3,7,4,3,1,2]
[3,4,7,4,3,1,3,4,7,4,3,1,2,3,4,7,4,3,1,3,4,7,4,3,1,2]
[4,3,7,3,4,1,4,3,7,3,4,1,2,4,3,7,3,4,1,4,3,7,3,4,1,2]
[3,4,7,3,4,1,3,4,7,3,4,1,2,3,4,7,3,4,1,3,4,7,3,4,1,2]
[3,5,4,5,3,1,2,2,1,3,5,4,5,3,1,2,3,5,4,5,3,1,2,2,1,3,5,4,5,3,1,2]
[3,5,5,3,4,1,2,1,4,3,5,5,3,4,1,2,3,5,5,3,4,1,2,1,4,3,5,5,3,4,1,2]
[5,4,7,4,3,3,1,2,5,4,7,4,3,3,1,2,5,4,7,4,3,3,1,2,5,4,7,4,3,3,1,2]
[4,7,4,5,3,3,1,2,4,7,4,5,3,3,1,2,4,7,4,5,3,3,1,2,4,7,4,5,3,3,1,2]
[5,4,7,3,4,3,1,2,5,4,7,3,4,3,1,2,5,4,7,3,4,3,1,2,5,4,7,3,4,3,1,2]
[3,5,4,7,4,3,1,_2735,3,5,4,7,4,3,1,2,3,5,4,7,4,3,1,_2735,3,5,4,7,4,3,1,2]
196660ms
| ?- time(call_nth( (
length(Xs0,N),m(Xs0,Xs0),
writeq(Xs0),nl ), 10)).
[4,7,4,3,1,4,7,4,3,1,2]
[4,7,3,4,1,4,7,3,4,1,2]
[5,4,7,4,3,1,_2371,5,4,7,4,3,1,2]
[4,7,4,5,3,1,_2371,4,7,4,5,3,1,2]
[5,4,7,3,4,1,_2371,5,4,7,3,4,1,2]
[3,5,4,7,4,1,2,3,5,4,7,4,1,2]
[4,3,7,4,5,1,2,4,3,7,4,5,1,2]
[3,4,7,4,5,1,2,3,4,7,4,5,1,2]
[4,7,5,3,6,4,1,4,7,5,3,6,4,2]
[5,4,7,4,3,6,1,5,4,7,4,3,6,2]
6550ms
| ?- time(call_nth( (
length(Xs0,N),reverse(Xs0,Ys),m(Xs0,Ys),
writeq(Ys),nl ), 10)).
[2,1,3,4,7,1,3,4,7]
[2,1,4,3,7,1,4,3,7]
[2,1,3,5,4,7,_2633,1,3,5,4,7]
[2,1,5,4,7,3,2,1,5,4,7,3]
[2,4,6,3,5,7,1,4,6,3,5,7]
[2,6,3,5,4,7,1,6,3,5,4,7]
[2,_2633,1,5,3,4,7,_2633,1,5,3,4,7]
[2,_2633,1,5,4,3,7,_2633,1,5,4,3,7]
[2,1,3,4,4,4,7,1,3,4,4,4,7]
[2,1,3,4,5,6,7,1,3,4,5,6,7]
1500ms
这是@Celelibi 改进版本的另一项改进 ( cele_n)。粗略地说，它通过限制第一个参数的长度获得了两倍，通过预先测试两个版本获得了另一个两倍。
cele_n SICStus 2.630s
cele_n SWI 12.258s 39,546,768 inferences
cele_2 SICStus 0.490s
cele_2 SWI 2.665s 9,074,970 inferences
appendh([], [], Xs, Xs).
appendh([_, _ | Ws], [X | Xs], Ys, [X | Zs]) :-
appendh(Ws, Xs, Ys, Zs).
m([H|A], X) :-
A = [_|_], % New
m(H, X, A).
m(1, X, A) :-
append(X, [2], A).
m(3, X, A) :-
appendh(X, B, B, X),
m(A, B).
m(4, X, A) :-
reverse(X, B),
m(A, B).
m(5, X, A) :-
X = [_| _],
m(A, [_|X]).
m(H1, [H2 | B], A) :-
\+ \+ ( H2 = 1 ; H2 = 2 ), % New
m(A, B),
( H1 = 6, H2 = 1
; H1 = 7, H2 = 2
).
answer3(X) :-
between(1, 13, N),
length(X, N),
reverse(X, A),
m(X, A).
run :-
time(findall(X, (answer3(X), write(X), nl), _)).