I have this hypothetical program to check if a path exists from point A to B.
/*city rules*/
edge(phx, tuc).
edge(tuc, ccg).
edge(ccg, sf).
connected(C1, C2) :-
edge(C1, C2).
connected(C1, C2) :-
edge(C1, X),
connected(X, C2).
the problem is it returns true, then false. Where is the false coming from?
Let's look at the exact reply you got from Prolog! First you got a single true and on pressing SPACE or ; you eventually got:
?- connected(phx,sf).
true
; false.
So you got true ; false. as the complete answer. The ; means "or". So Prolog essentially says: Your query connected(phx,sf). is the same as true ; false. So you need to look at the entire answer to understand what it means. Of course that is a bit odd, when true. would be good enough.
But first let's have another example:
?- connected(phx,X).
X = tuc
; X = ccg
; X = sf
; false.
Here Prolog's complete answer is: connected(phx,X). describes the same set of solutions as X = tuc ; X = ccg ; X = fg ; false. which again would be shorter if false would be omitted.
So why does Prolog write out this false? Prolog computes the answers incrementally. It first shows you X = tuc and waits what you would do. In a sense, it is a bit lazy not to show you everything at once. Sometimes, Prolog does know that there will be no further answer, in that case, it writes a dot directly:
?- member(X,[1,2]).
X = 1
; X = 2.
Here Prolog says: dixi! I have spoken.
But sometimes, it is not that sure:
?- member(1,[1,2]).
true
; false.
After proving that 1 is a member, it stops, otherwise it would have to explore the list further.
So this ; false. means: After the last answer/solution, Prolog was not yet sure that everything has been explored. This might be an inefficiency, it might be an indication that something can be improved. However, never, ever take this as pretext to insert a cut into your program. The cut in another answer is completely malaprop. It is the source for many, many errors. Before starting to use cuts you really should learn the other, pure part of Prolog, first.
BTW: Here is a better definition for connected/2 which avoids infinite loops by using closure/3 (click on it to get the definition).
connected(C0,C) :-
edge(C0,C1)
closure0(edge,C1,C).
Related
A paper I'm reading says the following:
Plaisted [3] showed that it is possible to write formally correct
PROLOG programs using first-order predicate-calculus semantics and yet
derive nonsense results such as 3 < 2.
It is referring to the fact that Prologs didn't use the occurs check back then (the 1980s).
Unfortunately, the paper it cites is behind a paywall. I'd still like to see an example such as this. Intuitively, it feels like the omission of the occurs check just expands the universe of structures to include circular ones (but this intuition must be wrong, according to the author).
I hope this example isn't
smaller(3, 2) :- X = f(X).
That would be disappointing.
Here is the example from the paper in modern syntax:
three_less_than_two :-
less_than(s(X), X).
less_than(X, s(X)).
Indeed we get:
?- three_less_than_two.
true.
Because:
?- less_than(s(X), X).
X = s(s(X)).
Specifically, this explains the choice of 3 and 2 in the query: Given X = s(s(X)) the value of s(X) is "three-ish" (it contains three occurrences of s if you don't unfold the inner X), while X itself is "two-ish".
Enabling the occurs check gets us back to logical behavior:
?- set_prolog_flag(occurs_check, true).
true.
?- three_less_than_two.
false.
?- less_than(s(X), X).
false.
So this is indeed along the lines of
arbitrary_statement :-
arbitrary_unification_without_occurs_check.
I believe this is the relevant part of the paper you can't see for yourself (no paywall restricted me from viewing it when using Google Scholar, you should try accessing this that way):
Ok, how does the given example work?
If I write it down:
sm(s(s(s(z))),s(s(z))) :- sm(s(X),X). % 3 < 2 :- s(X) < X
sm(X,s(X)). % forall X: X < s(X)
Query:
?- sm(s(s(s(z))),s(s(z)))
That's an infinite loop!
Turn it around
sm(X,s(X)). % forall X: X < s(X)
sm(s(s(s(z))),s(s(z))) :- sm(s(X),X). % 3 < 2 :- s(X) < X
?- sm(s(s(s(z))),s(s(z))).
true ;
true ;
true ;
true ;
true ;
true
The deep problem is that X should be Peano number. Once it's cyclic, one is no longer in Peano arithmetic. One has to add some \+cyclic_term(X) term in there. (maybe later, my mind is full now)
Can anybody explain the following code? I know it returns true if X is left of Y but I do not understand the stuff with the pipe, underscore and R. Does it mean all other elements of the array except X and Y?
left(X,Y,[X,Y|_]).
left(X,Y,[_|R]) :- left(X,Y,R).
If you are ever unsure about what a term "actually" denotes, you can use write_canonical/1 to obtain its canonical representation.
For example:
| ?- write_canonical([X,Y|_]).
'.'(_16,'.'(_17,_18))
and also:
| ?- write_canonical([a,b|c]).
'.'(a,'.'(b,c))
and in particular:
| ?- write_canonical([a|b]).
'.'(a,b)
This shows you that [a|b] is the term '.'(a,b), i.e., a term with functor . and two arguments.
To reinforce this point:
| ?- [a|b] == '.'(a,b).
yes
#mat answered the original question posted quite precisely and completely. However, it seems you have a bigger question, asked in the comment, about "What does the predicate definition mean?"
Your predicate, left(X, Y, L), defines a relation between two values, X and Y, and a list, L. This predicate is true (a query succeeds) if X is immediately left of Y in the list L.
There are two ways this can be true. One is that the first two elements in the list are X and Y. Thus, your first clause reads:
left(X, Y, [X,Y|_]).
This says that X is immediately left of Y in the list [X,Y|_]. Note that we do not care what the tail of the list is, as it's irrelevant in this case, so we use _. You could use R here (or any other variable name) and write it as left(X, Y, [X,Y|R]). and it would function properly. However, you would get a singleton variable warning because you used R only once without any other references to it. The warning appears since, in some cases, this might mean you have done this by mistake. Also note that [X,Y|_] is a list of at least two elements, so you can't just leave out _ and write [X,Y] which is a list of exactly two elements.
The above clause is not the only case for X to be immediately left of Y in the list. What if they are not the first two elements in the list? You can include another rule which says that X is immediately left of Y in a list if X is immediately left of Y in the tail of the list. This, along with the base case above, will cover all the possibilities and gives a complete recursive definition of left/3:
left(X, Y, [_|R]) :- left(X, Y, R).
Here, the list is [_|R] and the tail of the list is R.
This is about the pattern matching and about the execution mechanism of Prolog, which is built around the pattern matching.
Consider this:
1 ?- [user].
|: prove(T):- T = left(X,Y,[X,Y|_]).
|: prove(T):- T = left(X,Y,[_|R]), prove( left(X,Y,R) ).
|:
|: ^Z
true.
Here prove/1 emulates the Prolog workings proving a query T about your left/3 predicate.
A query is proven by matching it against a head of a rule, and proving that rule's body under the resulting substitution.
An empty body is considered proven right away, naturally.
prove(T):- T = left(X,Y,[X,Y|_]). encodes, "match the first rule's head. There's no body, so if the matching has succeeded, we're done."
prove(T):- T = left(X,Y,[_|R]), prove( left(X,Y,R) ). encodes, "match the second rule's head, and if successful, prove its body under the resulting substitution (which is implicit)".
Prolog's unification, =, performs the pattern matching whilst instantiating any logical variables found inside the terms being matched, according to what's being matched.
Thus we observe,
2 ?- prove( left( a,b,[x,a,b,c])).
true ;
false.
3 ?- prove( left( a,b,[x,a,j,b,c])).
false.
4 ?- prove( left( a,b,[x,a,b,a,b,c])).
true ;
true ;
false.
5 ?- prove( left( a,B,[x,a,b,a,b,c])).
B = b ;
B = b ;
false.
6 ?- prove( left( b,C,[x,a,b,a,b,c])).
C = a ;
C = c ;
false.
The ; is the key that we press to request the next solution from Prolog (while the Prolog pauses, awaiting our command).
I have this example:
descend(X,Y) :- child(X,Y).
descend(X,Y) :- child(X,Z), descend(Z,Y).
child(anne,bridget).
child(bridget,caroline).
child(caroline,donna).
It works great and I understand it. This is a solution of a little exercise. My solution was the same but changing:
descend(X,Y) :- descend(X,Z), descend(Z,Y).
That is, changing child for descend in the second descend rule.
If I query descend(X, Y). in the first solution, I obtain:
?- descend(X, Y).
X = anne,
Y = bridget ;
X = bridget,
Y = caroline ;
X = caroline,
Y = donna ;
X = anne,
Y = caroline ;
X = anne,
Y = donna ;
X = bridget,
Y = donna ;
false.
Which is correct. But if I query with my solution the same, I get:
?- descend(X, Y).
X = anne,
Y = bridget ;
X = bridget,
Y = caroline ;
X = caroline,
Y = donna ;
X = anne,
Y = caroline ;
X = anne,
Y = donna ;
ERROR: Out of local stack
It doesn't say X = bridget,Y = donna ; and it also overflows. I understand why it overflows. What I don't understand is why it doesn't find this last relationship. Is it because of the overflow? If so, why? (Why is the stack so big with such small knowledge base?).
If I query descend(bridget, donna) it answers yes.
I'm having problems imagining the exploration tree...
Apart from that question, I guess that the original solution is more efficient (ignoring the fact that mine enters in a infinite loop at the end), isn't it?
Thanks!
I'm having problems imagining the exploration tree...
Yes, that's quite difficult in Prolog. And it would be worse if you had a bigger database! But most of the time it is not necessary to envision the very precise search tree. Instead, you can use several quite robust notions.
Remember how you formulated your query. You looked at one solution after the other. But what you really were interested in was the question whether or not the query terminates. You can go for it without looking at the solutions by adding false.
?- descend(X, Y), false.
ERROR: Out of local stack
This query can never be true. It can either fail, overflow, or loop, or produce another error. What remains is a very useful notion: Universal termination or as in this case non-termination.
This can be extended to your actual program:
descend(X,Y) :- false, child(X,Y).
descend(X,Y) :- descend(X,Z), false, descend(Z,Y).
If this fragment called a failure-slice does not terminate, then also your original program does not terminate. Look at this miserable remainder of your program! Not even child/2 is present any longer. And thus we can conclude that child/2 does not influence non-termination! The Y occurs only once. And X will never cause a failure. Thus descend/2 terminates never!
So this conclusion is much more general than just a statement about a specific search tree. It's a statement about all of them.
If you still want to reason about the very precise order of solutions, you will have to go into the very gore of actual execution. But why bother? It's extremely complex, in particular if your child/2 relation contains cycles. Chances are that you will confuse things and build inaccurate theories (at least I did). No need for another cargo cult. I, for one, have given up to "step through" such myriads of detail. And I do not miss it.
So far, I have always taken steadfastness in Prolog programs to mean:
If, for a query Q, there is a subterm S, such that there is a term T that makes ?- S=T, Q. succeed although ?- Q, S=T. fails, then one of the predicates invoked by Q is not steadfast.
Intuitively, I thus took steadfastness to mean that we cannot use instantiations to "trick" a predicate into giving solutions that are otherwise not only never given, but rejected. Note the difference for nonterminating programs!
In particular, at least to me, logical-purity always implied steadfastness.
Example. To better understand the notion of steadfastness, consider an almost classical counterexample of this property that is frequently cited when introducing advanced students to operational aspects of Prolog, using a wrong definition of a relation between two integers and their maximum:
integer_integer_maximum(X, Y, Y) :-
Y >= X,
!.
integer_integer_maximum(X, _, X).
A glaring mistake in this—shall we say "wavering"—definition is, of course, that the following query incorrectly succeeds:
?- M = 0, integer_integer_maximum(0, 1, M).
M = 0. % wrong!
whereas exchanging the goals yields the correct answer:
?- integer_integer_maximum(0, 1, M), M = 0.
false.
A good solution of this problem is to rely on pure methods to describe the relation, using for example:
integer_integer_maximum(X, Y, M) :-
M #= max(X, Y).
This works correctly in both cases, and can even be used in more situations:
?- integer_integer_maximum(0, 1, M), M = 0.
false.
?- M = 0, integer_integer_maximum(0, 1, M).
false.
| ?- X in 0..2, Y in 3..4, integer_integer_maximum(X, Y, M).
X in 0..2,
Y in 3..4,
M in 3..4 ? ;
no
Now the paper Coding Guidelines for Prolog by Covington et al., co-authored by the very inventor of the notion, Richard O'Keefe, contains the following section:
5.1 Predicates must be steadfast.
Any decent predicate must be “steadfast,” i.e., must work correctly if its output variable already happens to be instantiated to the output value (O’Keefe 1990).
That is,
?- foo(X), X = x.
and
?- foo(x).
must succeed under exactly the same conditions and have the same side effects.
Failure to do so is only tolerable for auxiliary predicates whose call patterns are
strongly constrained by the main predicates.
Thus, the definition given in the cited paper is considerably stricter than what I stated above.
For example, consider the pure Prolog program:
nat(s(X)) :- nat(X).
nat(0).
Now we are in the following situation:
?- nat(0).
true.
?- nat(X), X = 0.
nontermination
This clearly violates the property of succeeding under exactly the same conditions, because one of the queries no longer succeeds at all.
Hence my question: Should we call the above program not steadfast? Please justify your answer with an explanation of the intention behind steadfastness and its definition in the available literature, its relation to logical-purity as well as relevant termination notions.
In 'The craft of prolog' page 96 Richard O'Keef says 'we call the property of refusing to give wrong answers even when the query has an unexpected form (typically supplying values for what we normally think of as inputs*) steadfastness'
*I am not sure if this should be outputs. i.e. in your query ?- M = 0, integer_integer_maximum(0, 1, M). M = 0. % wrong! M is used as an input but the clause has been designed for it to be an output.
In nat(X), X = 0. we are using X as an output variable not an input variable, but it has not given a wrong answer, as it does not give any answer. So I think under that definition it could be steadfast.
A rule of thumb he gives is 'postpone output unification until after the cut.' Here we have not got a cut, but we still want to postpone the unification.
However I would of thought it would be sensible to have the base case first rather than the recursive case, so that nat(X), X = 0. would initially succeed .. but you would still have other problems..
Disclaimer: This is informal and non-assessed coursework to do in my own time. I have tried it myself, failed and am now looking for some guidance.
I am trying to implement a version of the member/2 function which will only return members for a list once.
For example:
| ?- member(X, [1,2,3,1]).
X = 1 ? ;
X = 2 ? ;
X = 3 ? ;
X = 1 ? ;
I would like it to only print out each number a maximum of once.
| ?- once_member(X, [1,2,3,1]).
X = 1 ? ;
X = 2 ? ;
X = 3 ? ;
no
We have been told to do this with the cut '!' operator but I have looked over the notes for my course for cut and more online and yet still can't make it click in my head!
So far I have managed to get:
once_member(E, [E | L]) :- !.
once_member(E, [_, L]) :-
once_member(E, L).
Which returns 1 and then nothing else, I feel like my cut is in the wrong place and preventing a backtrack for each possible match but I'm really not sure where to go with it next.
I have looked in my course notes and also at: http://www.cs.ubbcluj.ro/~csatol/log_funk/prolog/slides/5-cuts.pdf and Programming in Prolog (Google Books)
Guidance on how to logically apply the cut would be most useful, but the answer might help me figure that out myself.
We have also been told to do another method which uses '\+' negation by failure but hopefully this may be simpler once cut has twigged for me?
Remove redundant answers and stay pure!
We define memberd/2 based on if_/3 and (=)/3:
memberd(X, [E|Es]) :-
if_(X = E, true, memberd(X, Es)).
Particularly with meta-predicates, a different argument order may come in handy sometimes:
list_memberd(Es, X) :-
memberd(X, Es).
Sample query:
?- memberd(X, [1,2,3,1]).
X = 1 ;
X = 2 ;
X = 3 ;
false.
The solution with cut... at first it sounds quite troublesome.
Assuming that the first argument will be instantiated, a solution is trivial:
once_member(X,L):-
member(X,L),!.
but this will not have the behavior you want if the first arg is not instantiated.
If we know the domain of the lists elements (for example numbers between 1 and 42) we could instantiate the first argument:
once_member(X,L):-
between(1,42,X),
member_(X,L).
member_(X,L):-
member(X,L),!.
but this is veeery inefficient
at this point, I started to believe that it's not possible to do with just a cut (assuming that we dont use + or list_to_set/2
oh wait! < insert idea emoticon here >
If we could implement a predicate (like list_to_set/2 of swi-prolog) that would take a list and produce a list in which all the duplicate elements are removed we could simply use the normal member/2 and don't get duplicate results. Give it a try, I think that you will be able to write it yourself.
--------Spoilers------------
one_member(X,L):-
list_to_set(L,S),
member(X,S).
list_to_set([],[]).
list_to_set([H|T],[H|S]):-
remove_all(H,T,TT),
list_to_set(TT,S).
%remove_all(X,L,S): S is L if we remove all instances of X
remove_all(_,[],[]).
remove_all(X,[X|T],TT):-
remove_all(X,T,TT),!.
remove_all(X,[H|T],[H|TT]):-
remove_all(X,T,TT).
As you see we have to use a cut in remove_all/3 because otherwise the third clause can be matched by remove_all(X,[X|_],_) since we do not specify that H is different from X. I believe that the solution with not is trivial.
Btw, the solution with not could be characterized as more declarative than the solution with cut; the cut we used is typically called a red cut since it alters the behavior of the program. And there are other problems; note that, even with the cut, remove_all(1,[1,2],[1,2]) would succeed.
On the other hand it's not efficient to check twice for a condition. Therefore, the optimal would be to use the if-then-else structure (but I assume that you are not allowed to use it either; its implementation can be done with a cut).
On the other hand, there is another, easier implementation with not: you should not only check if X is member of the list but also if you have encountered it previously; so you will need an accumulator:
-------------Spoilers--------------------
once_member(X,L):-
once_member(X,L,[]).
once_member(X,[X|_T],A):-
\+once_member(X,A).
once_member(X,[H|T],A):-
once_member(X,T,[H|A]).
once_member(X, Xs) :-
sort(Xs, Ys),
member(X, Ys).
Like almost all other solutions posted, this has some anomalies.
?- X = 1, once_member(X, [A,B]).
X = A, A = 1
; X = B, B = 1.
?- X = 1, once_member(X, [A,A]).
X = A, A = 1.
Here's an approach that uses a cut in the definition of once_member/2 together with the classic member/2 predicate:
once_member(X,[H|T]) :-
member(H,T),
!,
once_member(X,T).
once_member(H,[H|_]).
once_member(X,[_|T]) :-
once_member(X,T).
Applied to the example above:
?- once_member(X,[1,2,3,1]).
X = 2 ;
X = 3 ;
X = 1 ;
no
Note: Despite the odd-appearing three clause definition, once_member/2 is last-call/tail-recursive optimization eligible due to the placement of the cut ahead of its first self-invocation.