I am trying to understand why Prolog implementations do not behave according to the execution model in textbooks -- for example, the one in the book by Sterling and Shapiro's "The Art of Prolog" (chapter 6, "Pure Prolog", section 6.1, "The Execution Model of Prolog").
The execution model to which I refer is this (page 93 of Sterling & Shapiro):
Input: A goal G and a program P
Output: An instance of G that is a logical consequence of P, or no otherwise
Algorithm:
Initialize resolvent to the goal G
while resolvent not empty:
choose goal A from resolvent
choose renamed clause A' <- B_1, ..., B_n from P
such that A, A' unify with mgu θ
(if no such goal and clause exist, exit the "while" loop)
replace A by B_1, ..., B_n in resolvent
apply θ to resolvent and to G
If resolvent empty, then output G, else output NO
Additionally (page 120 of the same book), Prolog chooses goals (choose goal A) in left-to-right order, and searches clauses (choose renamed clause ...) in the order they show up in the program.
The program below has a definition of not (called n in the program) and one single fact.
n(X) :- X, !, fail.
n(X).
f(a).
If I try to prove n(n(f(X))), it succeeds (according to two textbooks and also on SWI Prolog, GNU Prolog and Yap). But isn't this a bit strange? According to that execution model, which several books expose, this is what I would expect to happen (skipping renaming of variables to keep things simple, since there would be no conflict anyway):
RESOLVENT: n(n(f(Z)))
unification matches X in first clause with n(f(Z)), and replaces the goal with the tail of that clause.
RESOLVENT: n(f(Z)), !, fail.
unification matches again X in the first clause with f(Z), and replaces the first goal in the resolvent with the tail of the clause
RESOLVENT: f(Z), !, fail, !, fail.
unification matches f(Z) -> success! Now this is eliminated from the resolvent.
RESOLVENT: !, fail, !, fail.
And "!, fail, !, fail" should not succeed! After the cut there is a fail. End of story. (And indeed, entering !,fail,!,fail as a query will fail in all Prolog systems that I have access to).
So may I presume that the execution model in textbooks is not precisely what Prolog uses?
edit: changing the first clause to n(X) :- call(X), !, fail makes no difference in all Prologs I tried.
Your program is not a pure Prolog program, since it contains a !/0 in n/1. You may ask yourself the simpler question: With your definitions, why does the query ?- n(f(X)). fail although there clearly is a fact n(X) in your program, meaning that n(X) is true for every X, and should therefore hold in particular for f(X) as well? This is because the program's clauses can no longer be considered in isolation due to the usage of !/0, and the execution model for pure Prolog cannot be used. A more modern and pure alternative for such impure predicates are often constraints, for example dif/2, with which you can constrain a variable to be distinct from a term.
The caption below does tell you what this particular algorithm is about:
Figure 4.2 An abstract interpreter for logic programs
Also, its description reads:
Output: An instance of G that is a logical consequence of P, or no otherwise.
That is, the algorithm in 4.2 only shows you how to compute a logical consequence for logic programs. It only gives you an idea for how Prolog actually works. And in particular cannot explain the !. Also, the algorithm in 4.2 is only able to explain how one solution ("consequence") is found, but Prolog tries to find all of them in a systematic manner called chronological backtracking. The cut interferes with chronological backtracking in a very particular manner which cannot be explained at the level of this algorithm.
You wrote:
Additionally (page 120 of the same book), Prolog chooses goals (choose goal A) in left-to-right order, and searches clauses (choose renamed clause ...) in the order they show up in the program.
That misses one important point which you can read on page 120:
Prolog's execution mechanism is obtained from the abstract interpreter by choosing the leftmost goal ... and replacing the non-deterministic choice of a clause by sequential search for a unifiable clause and backtracking.
So it is this little addition "and backtracking" which makes things more complex. You cannot see this in the abstract algorithm.
Here is a tiny example to show that backtracking is not explicitly handled in the algorithm.
p :-
q(X),
r(X).
q(1).
q(2).
r(2).
We would start with p which is rewritten to q(X), r(X) (there is no other way to continue).
Then, q(X) is selected, and θ = {X = 1}. So we have r(1) as the resolvent. But now, we do not have any matching clause, so we "exit the while loop" and answer no.
But wait, there is a solution! So how do we get it? When q(X) was selected, there was also another option for θ, i.e. θ = {X = 2}. The algorithm itself is not explicit about the mechanism to perform this operation. It only says: If you make the right choice everywhere, you will find an answer. To get a real algorithm out of that abstract one, we thus need some mechanism to do this.
When you reach the last step:
RESOLVENT: !, fail, !, fail
the cut ! here means, "erase everything". So the resolvent becomes empty. (this is faking it of course, but is close enough). cuts have no meaning at all here, the first fail says to flip the decision, and 2nd fail to flip it back. Now resolvent is empty - the decision was "YES", and remains so, twice flipped. (this is also faking it ... the "flipping" only makes sense in the presence of backtracking).
You can't of course place a cut ! on the list of goals in the resolvent, as it is not just one of the goals to fulfill. It has an operational meaning, it normally says "stop trying other choices" but this interpreter keeps no track of any choices (it "as if" makes all the choices at once). fail is not just a goal to fulfill too, it says "where you've succeeded say that you didn't, and vice versa".
So may I presume that the execution model in textbooks is not precisely what Prolog uses?
yes of course, the real Prologs have cut and fail unlike the abstract interpreter that you referred to. That interpreter has no explicit backtracking and instead has multiple successes by magic (its choice is inherently non-deterministic as if all the choices are made at once, in parallel - real Prologs only emulate that through sequential execution with explicit backtracking, to which the cut is referring - it simply has no meaning otherwise).
I think you got it almost right. The problem is here:
RESOLVENT: !, fail, !, fail.
The first ! and fail are from the second time that the first clause was matched. The other two are from the first time.
RESOLVENT: ![2], fail[2], ![1], fail[1].
The cut and fail have effect on the clause that is being processed -- NOT on the clause that "called" it. If you work through the steps again, but using these annotations, you'll get the right result.
![2], fail[2] makes the second call to n fail without backtracking. But the other call (the first) can still backtrack -- and it will:
RESOLVENT: n(_)
And the result is "yes".
This shows that Prolog keeps information about backtracking using a stack discipline. You may be interested in the the virtual machine that is used as a model for Prolog implementations. It is quite more complex than the execution model you mentioned, but the translation of Prolog into the VM will give you a much more accurate understanding of how Prolog works. This is the Warren Abstract Machine (WAM). The tutorial by Hasan Aït-Kaci is the best explanation you'll find for it (and it explains the cut, which if I remember correctly was absent from the original WAM description). If you are not used to abstract theoretical texts, you may try reading the text by Peter van Roy first: "1983-1993: the wonder years of sequential Prolog implementation". This article is clear and basically goes through the history of Prolog implementations, but giving special attention to the WAM. However, it does not show how the cut is implemented. If you carefully read it, however, you may be able to pick up Hasan's tutorial and read the section in which he implements the cut.
You have an extra level of nesting in your test goal:
n(n(f(X))
instead of:
n(f(X))
And indeed, if we try that, it works as expected:
$ prolog
GNU Prolog 1.3.0
By Daniel Diaz
Copyright (C) 1999-2007 Daniel Diaz
| ?- [user].
compiling user for byte code...
n(X) :- call(X), !, fail.
n(_X).
f(a).
user compiled, 4 lines read - 484 bytes written, 30441 ms
yes
| ?- f(a).
yes
| ?- n(f(a)).
no
| ?- n(f(42)).
yes
| ?- n(n(f(X))).
yes
| ?- n(f(X)).
no
| ?- halt.
So your understanding of Prolog is correct, your test case was not!
Updated
Showing the effects of negations of negations:
$ prolog
GNU Prolog 1.3.0
By Daniel Diaz
Copyright (C) 1999-2007 Daniel Diaz
| ?- [user].
compiling user for byte code...
n(X) :- format( "Resolving n/1 with ~q\n", [X] ), call(X), !, fail.
n(_X).
f(a) :- format( "Resolving f(a)\n", [] ).
user compiled, 4 lines read - 2504 bytes written, 42137 ms
(4 ms) yes
| ?- n(f(a)).
Resolving n/1 with f(a)
Resolving f(a)
no
| ?- n(n(f(a))).
Resolving n/1 with n(f(a))
Resolving n/1 with f(a)
Resolving f(a)
yes
| ?- n(n(n(f(a)))).
Resolving n/1 with n(n(f(a)))
Resolving n/1 with n(f(a))
Resolving n/1 with f(a)
Resolving f(a)
no
| ?- n(n(n(n(f(a))))).
Resolving n/1 with n(n(n(f(a))))
Resolving n/1 with n(n(f(a)))
Resolving n/1 with n(f(a))
Resolving n/1 with f(a)
Resolving f(a)
yes
| ?- halt.
While mat is right in that your program is not pure prolog (and this is relevant as the title of the chapter is Pure Prolog), not only since you use a cut but also since you write predicates that handle other predicates (pure prolog is a subset of first order logic) this is not the main issue; you are just missing backtracking
While you indeed have a cut, this will not be reached until goal n(f(X)) succeeds. However, as you know, this will fail and therefore prolog will backtrack and match the second clause.
I do not see how that would contradict with the model described in 6.1 (and would find it hard to believe that other books would describe a model where the execution would continue after failing and thus allow for the cut to prune the other solutions). In any case, I find that jumping to the conclusion that "Prolog implementations do no behave according to the execution model in textbooks" is quite similar to "there is a bug to the compiler", especially since the "counter-example" behaves as it should (not(not(true)) should be true)
Related
In Prolog we can write very simple programs like this:
mammal(dog).
mammal(cat).
animal(X) :- mammal(X).
The last line uses the symbol :- which informally lets us read the final fact as: if X is a mammal then it is also an animal.
I am beginning to learn Prolog and trying to establish which of the following is meant by the symbol :-
Implies (⇒)
Entails (⊨)
Provable (⊢)
In addition, I am not clear on the difference between these three. I am trying to read threads like this one, but the discussion is at a level above my capability, https://math.stackexchange.com/questions/286077/implies-rightarrow-vs-entails-models-vs-provable-vdash.
My thinking:
Prolog works by pattern-matching symbols (unification and search) and so we might be tempted to say the symbol :- means 'syntactic entailment'. However this would only be true of queries that are proven to be true as a result of that syntactic process.
The symbol :- is used to create a database of facts, and therefore is semantic in nature. That means it could be one of Implies (⇒) or Entails (⊨) but I don't know which.
Neither. Or, rather if at all, then it's the implication. The other symbols are above, that is meta-language. The Mathematics Stack Exchange answers explain this quite nicely.
So why :- is not that much of an implication, consider:
p :- p.
In logic, both truth values make this a valid sentence. But in Prolog we stick to the minimal model. So p is false. Prolog uses a subset of predicate logic such that there actually is only one minimal model. And worse, Prolog's actual default execution strategy makes this an infinite loop.
Nevertheless, the most intuitive way to read LHS :- RHS. is to see it as a way to generate new knowledge. Provided RHS is true it follows that also LHS is true. This way one avoids all the paradoxa related to implication.
The direction right-to-left is a bit counter intuitive. This direction is motivated by Prolog's actual execution strategy (which goes left-to-right in this representation).
:- is usually read as if, so something like:
a :- b, c .
reads as
| a is true if b and c are true.
In formal logic, the above would be written as
| a ← b ∧ c
Or
| b and c imply a
I am reading through Learn Prolog Now! 's chapter on cuts and at the same time Bratko's Prolog Programming for Artificial Intelligence, Chapter 5: Controlling Backtracking. At first it seemed that a cut was a straight-forward way to mimic an if-else clause known from other programming languages, e.g.
# Find the largest number
max(X,Y,Y):- X =< Y,!.
max(X,Y,X).
However, as is noted down the line this code will fail in cases where all variables are instantiated even when we expect false, e.g.
?- max(2,3,2).
true.
The reason is clear: the first rule fails, the second does not have any conditions connected to it anymore, so it will succeed. I understand that, but then a solution is proposed (here's a swish):
max(X,Y,Z):- X =< Y,!, Y = Z.
max(X,Y,X).
And I'm confused how I should read this. I thought ! meant: 'if everything that comes before this ! is true, stop termination including any other rules with the same predicate'. That can't be right, though, because that would mean that the instantiation of Y = Z only happens in case of failure, which would be useless for that rule.
So how should a cut be read in a 'human' way? And, as an extension, how should I read the proposed solution for max/3 above?
See also this answer and this question.
how should I read the proposed solution for max/3 above?
max(X,Y,Z):- X =< Y, !, Y = Z.
max(X,Y,X).
You can read this as follows:
When X =< Y, forget the second clause of the predicate, and unify Y and Z.
The cut throws away choice points. Choice points are marks in the proof tree that tell Prolog where to resume the search for more solutions after finding a solution. So the cut cuts away parts of the proof tree. The first link above (here it is again) discusses cuts in some detail, but big part of that answer is just citing what others have said about cuts elsewhere.
I guess the take home message is that once you put a cut in a Prolog program, you force yourself to read it operationally instead of declaratively. In order to understand which parts of the proof tree will be cut away, you (the programmer) have to go through the motions, consider the order of the clauses, consider which subgoals can create choice points, consider which solutions are lost. You need to build the proof tree (instead of letting Prolog do it).
There are many techniques you can use to avoid creating choice points you know you don't need. This however is a bit of a large topic. You should read the available material and ask specific questions.
The problem with your code is that the cut is never reached when evaluating your query.
The first step of trying to evaluate a goal with a rule is pattern matching.
The goal max(2,3,2) doesn't match the pattern max(X,Y,Y), since the second and third arguments are the same in the pattern and 3 and 2 don't pattern-match with each other. As such, this rule has already failed at the pattern matching stage, thus the evaluator doesn't get as far as testing X =< Y, let alone reaching the !.
But your understanding of cuts is pretty much correct. Given this code
a(X) :- b(X).
a(X) :- c(X).
b(X) :- d(X), !.
b(X) :- e(X).
c(3).
d(4).
d(5).
e(6).
and the goal
?- a(X).
The interpreter will begin with the first rule, by trying to satisfy b(X). In the process, it discovers that d(4) provides a solution, so binds the value 4 to X. Then the cut kicks in, which discards the backtracking on b(X), thus no further solutions to b(X) are found. However, it does not remove the backtracking on a(X), therefore if you ask Prolog to find another solution then it will find X = 3 through the a(X) :- c(X). rule. If you changed the first rule to a(X) :- b(X), !. then it would fail to find X = 3.
Although the cut means no X = 5 solution is found, if your query is
?- a(5).
then the interpreter will return true. This is because the a(5) calls b(5), which calls d(5), which is defined to be true. The d(4) fact fails pattern matching, therefore it does not trigger the cut like it does when querying a(X).
This is an example of a red cut (see my comment on user1812457's answer). Perhaps a good reason to avoid red cuts, besides them breaking logical purity, is to avoid bugs resulting from this behaviour.
I am just learning prolog and there is a thing I can't get my head over.
Suppose I have the following program
value(v).
a(X) :- not(value(X)).
So a(v). gives me false, as value(v) can be proved correct.
a(w) gives me true, as there is no fact value(w), therefore, even when trying, it can't be proved correct.
In my understanding, requesting a(X). should give me the first possible value that makes value(X) unproveable. There should be an infinite amount of possibilities, as only value(v) is correct.
But why does Prolog keep answering false?
First of all, please use the ISO predicate (\+)/1 instead of not/1.
Second, please don't use (\+)/1 to denote disequality of terms: (\+)/1 is incomplete in Prolog, and thus not logically sound. It is not logical negation, but rather denotes "not provable".
In your case: ?- value(X). succeeds, so it is provable, so ?- \+ value(X). fails although there are instantiations that make the query succeed.
In particular, ?- \+ value(a). succeeds.
So we have:
?- \+ value(V).
false.
But a more specific query succeeds:
?- V = a, \+ value(V).
V = a.
This obviously runs counter to logical properties we expect from pure relations. See logical-purity.
To denote disequality of terms, use dif/2. If your Prolog system does not support dif/2, ask for its inclusion, or use iso_dif/2 as a safe approximation that is logically sound. See prolog-dif for more information.
Prolog operates under "closed world assumption" – it only knows what we told it about. In particular, we've told it nothing about no w, u, or any other stuff, so how could it produce them to us? And why should w come before u, and not vice versa?
The only thing sensible could be to produce (X, dif(X,v)), but it would be the answer to a different question, namely, "how to make a(X) provable?", not the one Prolog is actually answering, namely "is a(X) provable?".
To ease up your cognitive burden, rename the Prolog prompt's replies in your head from true to Yes, and from false to No.
Yes would mean Prolog telling us "yes, I could prove it!", and No – "no, I couldn't prove it."
Also rename "not" to read \+ as not_provable, mentally.
This is probably the most trivial implementation of a function that returns the length of a list in Prolog
count([], 0).
count([_|B], T) :- count(B, U), T is U + 1.
one thing about Prolog that I still cannot wrap my head around is the flexibility of using variables as parameters.
So for example I can run count([a, b, c], 3). and get true. I can also run count([a, b], X). and get an answer X = 2.. Oddly (at least for me) is that I can also run count(X, 3). and get at least one result, which looks something like X = [_G4337877, _G4337880, _G4337883] ; before the interpreter disappears into an infinite loop. I can even run something truly "flexible" like count(X, A). and get X = [], A = 0 ; X = [_G4369400], A = 1., which is obviously incomplete but somehow really nice.
Therefore my multifaceted question. Can I somehow explain to Prolog not to look beyond first result when executing count(X, 3).? Can I somehow make Prolog generate any number of solutions for count(X, A).? Is there a limitation of what kind of solutions I can generate? What is it about this specific predicate, that prevents me from generating all solutions for all possible kinds of queries?
This is probably the most trivial implementation
Depends from viewpoint: consider
count(L,C) :- length(L,C).
Shorter and functional. And this one also works for your use case.
edit
library CLP(FD) allows for
:- use_module(library(clpfd)).
count([], 0).
count([_|B], T) :- U #>= 0, T #= U + 1, count(B, U).
?- count(X,3).
X = [_G2327, _G2498, _G2669] ;
false.
(further) answering to comments
It was clearly sarcasm
No, sorry for giving this impression. It was an attempt to give you a synthetic answer to your question. Every details of the implementation of length/2 - indeed much longer than your code - have been carefully weighted to give us a general and efficient building block.
There must be some general concept
I would call (full) Prolog such general concept. From the very start, Prolog requires us to solve computational tasks describing relations among predicate arguments. Once we have described our relations, we can query our 'knowledge database', and Prolog attempts to enumerate all answers, in a specific order.
High level concepts like unification and depth first search (backtracking) are keys in this model.
Now, I think you're looking for second order constructs like var/1, that allow us to reason about our predicates. Such constructs cannot be written in (pure) Prolog, and a growing school of thinking requires to avoid them, because are rather difficult to use. So I posted an alternative using CLP(FD), that effectively shields us in some situation. In this question specific context, it actually give us a simple and elegant solution.
I am not trying to re-implement length
Well, I'm aware of this, but since count/2 aliases length/2, why not study the reference model ? ( see source on SWI-Prolog site )
The answer you get for the query count(X,3) is actually not odd at all. You are asking which lists have a length of 3. And you get a list with 3 elements. The infinite loop appears because the variables B and U in the first goal of your recursive rule are unbound. You don't have anything before that goal that could fail. So it is always possible to follow the recursion. In the version of CapelliC you have 2 goals in the second rule before the recursion that fail if the second argument is smaller than 1. Maybe it becomes clearer if you consider this slightly altered version:
:- use_module(library(clpfd)).
count([], 0).
count([_|B], T) :-
T #> 0,
U #= T - 1,
count(B, U).
Your query
?- count(X,3).
will not match the first rule but the second one and continue recursively until the second argument is 0. At that point the first rule will match and yield the result:
X = [_A,_B,_C] ?
The head of the second rule will also match but its first goal will fail because T=0:
X = [_A,_B,_C] ? ;
no
In your above version however Prolog will try the recursive goal of the second rule because of the unbound variables B and U and hence loop infinitely.
Because Prolog uses chronological backtracking(from the Prolog Wikipedia page) even after an answer is found(in this example where there can only be one solution), would this justify Prolog as using eager evaluation?
mother_child(trude, sally).
father_child(tom, sally).
father_child(tom, erica).
father_child(mike, tom).
sibling(X, Y) :- parent_child(Z, X), parent_child(Z, Y).
parent_child(X, Y) :- father_child(X, Y).
parent_child(X, Y) :- mother_child(X, Y).
With the following output:
?- sibling(sally, erica).
true ;
false.
To summarize the discussion with #WillNess below, yes, Prolog is strict. However, Prolog's execution model and semantics are substantially different from the languages that are usually labelled strict or non-strict. For more about this, see below.
I'm not sure the question really applies to Prolog, because it doesn't really have the kind of implicit evaluation ordering that other languages have. Where this really comes into play in a language like Haskell, you might have an expression like:
f (g x) (h y)
In a strict language like ML, there is a defined evaluation order: g x will be evaluated, then h y, and f (g x) (h y) last. In a language like Haskell, g x and h y will only be evaluated as required ("non-strict" is more accurate than "lazy"). But in Prolog,
f(g(X), h(Y))
does not have the same meaning, because it isn't using a function notation. The query would be broken down into three parts, g(X, A), h(Y, B), and f(A,B,C), and those constituents can be placed in any order. The evaluation strategy is strict in the sense that what comes earlier in a sequence will be evaluated before what comes next, but it is non-strict in the sense that there is no requirement that variables be instantiated to ground terms before evaluation can proceed. Unification is perfectly content to complete without having given you values for every variable. I am bringing this up because you have to break down a complex, nested expression in another language into several expressions in Prolog.
Backtracking has nothing to do with it, as far as I can tell. I don't think backtracking to the nearest choice point and resuming from there precludes a non-strict evaluation method, it just happens that Prolog's is strict.
That Prolog pauses after giving each of the several correct answers to a problem has nothing to do with laziness; it is a part of its user interaction protocol. Each answer is calculated eagerly.
Sometimes there will be only one answer but Prolog doesn't know that in advance, so it waits for us to press ; to continue search, in hopes of finding another solution. Sometimes it is able to deduce it in advance and will just stop right away, but only sometimes.
update:
Prolog does no evaluation on its own. All terms are unevaluated, as if "quoted" in Lisp.
Prolog will unfold your predicate definitions as written and is perfectly happy to keep your data structures full of unevaluated uninstantiated holes, if so entailed by your predicate definitions.
Haskell does not need any values, a user does, when requesting an output.
Similarly, Prolog produces solutions one-by-one, as per the user requests.
Prolog can even be seen to be lazier than Haskell where all arithmetic is strict, i.e. immediate, whereas in Prolog you have to explicitly request the arithmetic evaluation, with is/2.
So perhaps the question is ill-posed. Prolog's operations model is just too different. There are no "results" nor "functions", for one; but viewed from another angle, everything is a result, and predicates are "multi"-functions.
As it stands, the question is not correct in what it states. Chronological backtracking does not mean that Prolog will necessarily backtrack "in an example where there can be only one solution".
Consider this:
foo(a, 1).
foo(b, 2).
foo(c, 3).
?- foo(b, X).
X = 2.
?- foo(X, 2).
X = b.
So this is an example that does have only one solution and Prolog recognizes that, and does not attempt to backtrack. There are cases in which you can implement a solution to a problem in a way that Prolog will not recognize that there is only one logical solution, but this is due to the implementation and is not inherent to Prolog's execution model.
You should read up on Prolog's execution model. From the Wikipedia article which you seem to cite, "Operationally, Prolog's execution strategy can be thought of as a generalization of function calls in other languages, one difference being that multiple clause heads can match a given call. In that case, [emphasis mine] the system creates a choice-point, unifies the goal with the clause head of the first alternative, and continues with the goals of that first alternative." Read Sterling and Shapiro's "The Art of Prolog" for a far more complete discussion of the subject.
from Wikipedia I got
In eager evaluation, an expression is evaluated as soon as it is bound to a variable.
Then I think there are 2 levels - at user level (our predicates) Prolog is not eager.
But it is at 'system' level, because variables are implemented as efficiently as possible.
Indeed, attributed variables are implemented to be lazy, and are rather 'orthogonal' to 'logic' Prolog variables.