Related
Main features
I recently have been looking to make a Prolog meta-interpreter with a certain set of features, but I am starting to see that I don't have the theoretical knowledge to work on it.
The features are as follows :
Depth-first search.
Interprets any non-recursive Prolog program the same way a classic interpreter would.
Guarantees breaking out of any infinite recursion. This most-likely means breaking Turing-completeness, and I'm okay with that.
As long as each step of the recursion reduces the complexity of the expression, keep evaluating it. To be more specific, I want predicates to be allowed to call themselves, but I want to prevent a clause to be able to call a similarly or more complex version of itself.
Obviously, (3) and (4) are the ones I am having problems with. I am not sure if those 2 features are compatible. I am not even sure if there is a way to define complexity such that (4) makes logical sense.
In my researches, I have come across the concept of "unavoidable pattern", which, I believe, provides a way to ensure feature (3), as long as feature (4) has a well-formed definition.
I specifically want to know if this kind of interpreter has been proven impossible, and, if not, if theoretical or concrete work on similar interpreters has been done in the past.
Extra features
Provided the above features are possible to implement, I have extra features I want to add, and would be grateful if you could enlighten me on the feasibility of such features as well :
Systematically characterize and describe those recursions, such that, when one is detected, a user-defined predicate or clause could be called that matches this specific form of recursion.
Detect patterns that result in an exponential number of combinatorial choices, prevent evaluation, and characterize them in the same way as step (5), such that they can be handled by a built-in or user-defined predicate.
Example
Here is a simple predicate that obviously results in infinite recursion in a normal Prolog interpreter in all but the simplest of cases. This interpreter should be able to evaluate it in at most PSPACE (and, I believe, at most P if (6) is possible to implement), while still giving relevant results.
eq(E, E).
eq(E, F):- eq(E,F0), eq(F0,F).
eq(A + B, AR + BR):- eq(A, AR), eq(B, BR).
eq(A + B, B + A).
eq(A * B, B * A).
eq((A * B) / B, A).
eq(E, R):- eq(R, E).
Example of results expected :
?- eq((a + c) + b, b + (c + a)).
true.
?- eq(a, (a * b) / C).
C = b.
The fact that this kind of interpreter might prove useful by the provided example hints me towards the fact that such an interpreter is probably impossible, but, if it is, I would like to be able to understand what makes it impossible (for example, does (3) + (4) reduce to the halting problem? is (6) NP?).
If you want to guarantee termination you can conservatively assume any input goal is nonterminating until proven otherwise, using a decidable proof procedure. Basically, define some small class of goals which you know halt, and expand it over time with clever ideas.
Here are three examples, which guarantee or force three different kinds of termination respectively (also see the Power of Prolog chapter on termination):
existential-existential: at least one answer is reached before potentially diverging
universal-existential: no branches diverge but there may be an infinite number of them, so the goal may not be universally terminating
universal-universal: after a finite number of steps, every answer will be reached, so in particular there must be a finite number of answers
In the following, halts(Goal) is assumed to correctly test a goal for existential-existential termination.
Existential-Existential
This uses halts/1 to prove existential termination of a modest class of goals. The current evaluator eval/1 just falls back to the underlying engine:
halts(halts(_)).
eval(Input) :- Input.
:- \+ \+ halts(halts(eval(_))).
safe_eval(Input) :-
halts(eval(Input)),
eval(Input).
?- eval((repeat, false)).
C-c C-cAction (h for help) ? a
abort
% Execution Aborted
?- safe_eval((repeat, false)).
false.
The optional but highly recommended goal directive \+ \+ halts(halts(eval(_))) ensures that halts will always halt when run on eval applied to anything.
The advantage of splitting the problem into a termination checker and an evaluator is that the two are decoupled: you can use any evaluation strategy you want. halts can be gradually augmented with more advanced methods to expand the class of allowed goals, which frees up eval to do the same, e.g. clause reordering based on static/runtime mode analysis, propagating failure, etc. eval can itself expand the class of allowed goals by improving termination properties which are understood by halts.
One caveat - inputs which use meta-logical predicates like var/1 could subvert the goal directive. Maybe just disallow such predicates at first, and again relax the restriction over time as you discover safe patterns of use.
Universal-Existential
This example uses a meta-interpreter, adapted from the Power of Prolog chapter on meta-interpreters, to prune off branches which can't be proven to existentially terminate:
eval(true).
eval((A,B)) :- eval(A), eval(B).
eval((A;_)) :- halts(eval(A)), eval(A).
eval((_;B)) :- halts(eval(B)), eval(B).
eval(g(Head)) :-
clause(Head, Body),
halts(eval(Body)),
eval(Body).
So here we're destroying branches, rather than refusing to evaluate the goal.
For improved efficiency, you could start by naively evaluating the input goal and building up per-branch sets of visited clause bodies (using e.g. clause/3), and only invoke halts when you are about to revisit a clause in the same branch.
Universal-Universal
The above meta-interpreter rules out at least all the diverging branches, but may still have an infinite number of individually terminating branches. If we want to ensure universal termination we can again do everything before entering eval, as in the existential-existential variation:
...
:- \+ \+ halts(halts(\+ \+ eval(_))).
...
safe_eval(Input) :-
halts(\+ \+ eval(Input)),
eval(Input).
So we're just adding in universal quantification.
One interesting thing you could try is running halts itself using eval. This could yield speedups, better termination properties, or qualitatively new capabilities, but would of course require the goal directive and halts to be written according to eval's semantics. E.g. if you remove double negations then \+ \+ would not universally quantify, and if you propagate false or otherwise don't conform to the default left-to-right strategy then the (goal, false) test for universal termination (PoP chapter on termination) also would not work.
I am currently trying to understand the basics of prolog.
I have a knowledge base like this:
p(a).
p(X) :- p(X).
If I enter the query p(b), the unification with the fact fails and the rule p(X) :- p(X) is used which leads the unification with the fact to fail again. Why is the rule applied over and over again after that? Couldn't prolog return false at this point?
After a certain time I get the message "Time limit exceeded".
I'm not quite sure why prolog uses the rule over and over again, but since it is, I don't understand why I get a different error message as in the following case.
To be clear, I do understand that "p(X) if p(X)" is an unreasonable rule, but I would like to understand what exactly happens there.
If I have a knowledge base like this:
p(X) :- p(X).
p(a).
There is no chance to come to a result even with p(a) because the fact is below the rule and the rule is called over and over again. For this variant I receive a different error message almost instantly "ERROR: Out of local stack" which is comprehensible.
Now my question - what is the difference between those cases?
Why am I receiving different error messages and why is prolog not returning false after the first application of the rule in the above case? My idea would be that in the above case the procedure is kind of restarted each time the rule gets called and in the below case the same procedure calls the rule over and over again. I would be grateful if somebody could elaborate this.
Update: If I query p(a). to the 2nd KB as said I receive "Out of local stack", but if I query p(b). to the same KB I get "Time limit exceeded". This is even more confusing to me, shouldn't the constant be irrelevant for the infinite loop?
Let us first consider the following program fragment that both examples have in common:
p(X) :- p(X).
As you correctly point out, it is obvious that no particular solutions are described by this fragment in isolation. Declaratively, we can read it as: "p(X) holds if p(X) holds". OK, so we cannot deduce any concrete solution from only this clause.
This explains why p(b) cannot hold if only this fragment is considered. Additionally, p(a) does not imply p(b) either, so no matter where you put the fact p(a), you will never derive p(b) from these two clauses.
Procedurally, Prolog still attempts to find cases where p(X) holds. So, if you post ?- p(X). as a query, Prolog will try to find a resolution refutation, disregarding what it has "already tried". For this reason, it will try to prove p(X) over and over. Prolog's default resolution strategy, SLDNF resolution, keeps no memory of which branches have already been tried, and also for this reason can be implemented very efficiently, with little overhead compared to other programming languages.
The difference between an infinite deduction attempt and an out of local stack error error can only be understood procedurally, by taking into account how Prolog executes these fragments.
Prolog systems typically apply an optimization that is called tail call optimization. This is applicable if no more choice-points remain, and means that it can discard (or reuse) existing stack frames.
The key difference between your two examples is obviously where you add the fact: Either before or after the recursive clause.
In your case, if the recursive clause comes last, then no more choice-points remain at the time the goal p(X) is invoked. For this reason, an existing stack frame can be reused or discarded.
On the other hand, if you write the recursive clause first, and then query ?- q(X). (or ?- q(a).), then both clauses are applicable, and Prolog remembers this by creating a choice-point. When the recursive goal is invoked, the choice-point still exists, and therefore the stack frames pile up until they exceed the available limits.
If you query ?- p(b)., then argument indexing detects that p(a) is not applicable, and again only the recursive clause applies, independent of whether you write it before or after the fact. This explains the difference between querying p(X) (or p(a)) and p(b) (or other queries). Note that Prolog implementations differ regarding the strength of their indexing mechanisms. In any case, you should expect your Prolog system to index at least on the outermost functor and arity of the first argument. If necessary, more complex indexing schemes can be constructed manually on top of this mechanism. Modern Prolog systems provide JIT indexing, deep indexing and other mechanisms, and so they often automatically detect the exact subset of clauses that are applicable.
Note that there is a special form of resolution called SLG resolution, which you can use to improve termination properties of your programs in such cases. For example, in SWI-Prolog, you can enable SLG resolution by adding the following directives before your program:
:- use_module(library(tabling)).
:- table p/1.
With these directives, we obtain:
?- p(X).
X = a.
?- p(b).
false.
This coincides with the declarative semantics you expect from your definitions. Several other Prolog systems provide similar facilities.
It should be easy to grasp the concept of infinite loop by studying how standard repeat/0 is implemented:
repeat.
repeat :- repeat.
This creates an infinite number of choice points. First clause, repeat., simply allows for a one time execution. The second clause, repeat :- repeat. makes it infinitely deep recursion.
Adding any number of parameters:
repeat(_, _, ..., _).
repeat(Param1, Param2, ..., ParamN) :- repeat(Param1, Param2, ..., ParamN).
You may have bodies added to these clauses and have parameters of the first class having meaningful names depending on what you are trying to archive. If bodies won't contain cuts, direct or inherited from predicates used, this will be an infinite loop too just as repeat/0.
There is a very detailed Draft proposal for setup_call_cleanup/3.
Let me quote the relevant part for my question:
c) The cleanup handler is called exactly once; no later than upon failure of G. Earlier moments are:
If G is true or false, C is called at an implementation dependent moment after the last solution and after the last observable effect of G.
And this example:
setup_call_cleanup(S=1,G=2,write(S+G)).
Succeeds, unifying S = 1, G = 2.
Either: outputs '1+2'
Or: outputs on backtracking '1+_' prior to failure.
Or (?): outputs on backtracking '1+2' prior to failure.
In my understanding, this is basically because a unification is a
backtrackable goal; it simply fails on reexecution. Therefore, it is
up to the implementation to decide whether to call the cleanup just
after the fist execution (because there will be no more observable
effects of the goal), or postpone until the second execution of the
goal which now fails.
So it seems to me that this cannot be used to detect determinism
portably. Only a few built-in constructs like true, fail, !
etc. are genuinely non-backtrackable.
Is there any other way to check determinism without executing a goal twice?
I'm currently using SWI-prolog's deterministic/1, but I'd certainly
appreciate portability.
No. setup_call_cleanup/3 cannot detect determinism in a portable manner. For this would restrict an implementation in its freedom. Systems have different ways how they implement indexing. They have different trade-offs. Some have only first argument indexing, others have more than that. But systems which offer "better" indexing behave often quite randomly. Some systems do indexing only for nonvar terms, others also permit clauses that simply have a variable in the head - provided it is the last clause. Some may do "manual" choice point avoidance with safe tests prior to cuts and others just omit this. Brief, this is really a non-functional issue, and insisting on portability in this area is tantamount to slowing systems down.
However, what still holds is this: If setup_call_cleanup/3 detects determinism, then there is no further need to use a second goal to determine determinism! So it can be used to implement determinism detection more efficiently. In the general case, however, you will have to execute a goal twice.
The current definition of setup_call_cleanup/3 was also crafted such as to permit an implementation to also remove unnecessary choicepoints dynamically.
It is thinkable (not that I have seen such an implementation) that upon success of Call and the internal presence of a choicepoint, an implementation may examine the current choicepoints and remove them if determinism could be detected. Another possibility might be to perform some asynchronous garbage collection in between. All these options are not excluded by the current specification. It is unclear if they will ever be implemented, but it might happen, once some applications depend on such a feature. This has happened in Prolog already a couple of times, so a repetition is not completely fantasy. In fact I am thinking of a particular case to help DCGs to become more determinate. Who knows, maybe you will go that path!
Here is an example how indexing in SWI depends on the history of previous queries:
?- [user].
p(_,a). p(_,b). end_of_file.
true.
?- p(1,a).
true ;
false.
?- p(_,a).
true.
?- p(1,a).
true. % now, it's determinate!
Here is an example, how indexing on the second argument is strictly weaker than first argument indexing:
?- [user].
q(_,_). q(0,0). end_of_file.
true.
?- q(X,1).
true ; % weak
false.
?- q(1,X).
true.
As you're interested in portability, Logtalk's lgtunit tool defines a portable deterministic/1 predicate for 10 of its supported backend Prolog compilers:
http://logtalk.org/library/lgtunit_0.html
https://github.com/LogtalkDotOrg/logtalk3/blob/master/tools/lgtunit/lgtunit.lgt (starting around line 1051)
Note that different systems use different built-in predicates that approximate the intended functionality.
How can I add a function (e.g., hammingweight) and use it in expressions occuring in the right-hand side is some (is)/2 goal?
Could something like goal_expansion or term_expansion help here?
I acknowledge that this is not a big feature, but it could increase readability of some of my Prolog programs.
Writing a custom (is)/2 predicate (implementing a custom expression evaluator) is do-able, but I would like to keep runtime overhead low, as I don't want to sacrifice readability for runtime overhead in this case.
There is no such provision in ISO Prolog, neither to extend (is)/2 nor to rely on goal expansion. And, looking at the various implementation specific features that are offered by some implementations to this end, there is no generally agreed upon way to do this. So implementing your own (my_is)/2 seems to be the best way to go.
Also note, that this would not only affect (is)/2 but also all other built-ins that use evaluable functors. In particular, all arithmetic comparison built-ins (8.7 Arithmetic comparison) (see this overview) would be affected.
My simple minded (~20 LOC) syntax sugar, lifter, it's based on goal_expansion.
With lifter, the clause
longer(A,B) :-
length(A,º) > length(B,º).
is expanded to
longer(A, B) :-
length(A, C),
length(B, D),
C > D.
You can use Logtalk's term-expansion mechanism, which is portable and works with its twelve supported Prolog compilers (*). Logtalk compiling and loading and loading predicates accept Prolog files and will output the corresponding Prolog expanded files. For example, assuming that the file you want to expand is named source.pl and that your term_expansion/2 and goal_expansion/2 predicate definitions are in a file named expansions.pl, you can do something like:
% first, load the expansion hooks:
| ?- [expansions].
...
% second, expand a file using those hooks:
| ?- logtalk_compile(source, [hook(user)]).
...
You will get the expanded file, which will be (by default) named source_pl.pl (in a directory that will depend on the value of the scratch_directory Logtalk flag). If the expansions are contained in a Prolog module, use above the module name instead of user. If the source.pl file contains a module instead of plain Prolog code, you'll need to define some clauses for the term_expansion/2 predicate to avoid Logtalk compiling the module as an object. But in the simpler case where you're not using modules, the two queries above should suffice.
One feature of Logtalk's term-expansion mechanism that might be useful is that you can mark a term or a goal to not be expanded or further expanded by wrapping it with the {}/1 control construct.
(*) Note that term-expansion mechanism are not standard, not provided by all Prolog implementations, and with significant differences between implementations.
Many Prolog systems don't allow user defined evaluable predicates.
Sometimes the problem is that the evaluable predicates live in
another namespace. Sometimes the Prolog system shyes away from jumping back into Prolog execution while doing an arithmetic evaluation in the host language.
Some Prolog systems have nevertheless user defined evaluable predicates, like ECLiPSe Prolog and Jekejeke Prolog. In Jekejeke Prolog the overhead was two fold. To my surprise in the new Dogelog runtime user definable evaluable
predicates show an advantage:
/* Dogelog Runtime 0.9.5 */
fact(0, 1) :- !.
fact(N, X) :- M is N-1, fact(M, Y), X is Y*N.
fact2(0, 1) :- !.
fact2(N, X) :- X is fact2(N-1)*N.
for(_).
for(N) :- N > 1, M is N - 1, for(M).
% ?- time((for(1000), fact(1000, _), fail; true)).
% % Wall 1595 ms, trim 0 ms
% ?- time((for(1000), _ is fact2(1000), fail; true)).
% % Wall 1394 ms, trim 0 ms
I am attributing the slight speed advantage to the more concise formulation in fact2/2. The formulation uses less Prolog logical variables. And the user defined evaluable predicates capable (is)/2 internally does also no Prolog logical variables, the host language assigments that happen do not allocate
a Prolog logical variable or trail the same, so that in the end there is a speed-up.
I often end up writing code in Prolog which involves some arithmetic calculation (or state information important throughout the program), by means of first obtaining the value stored in a predicate, then recalculating the value and finally storing the value using retractall and assert because in Prolog we cannot assign values to variable twice using is (thus making almost every variable that needs modification, global). I have come to know that this is not a good practice in Prolog. In this regard I would like to ask:
Why is it a bad practice in Prolog (though i myself don't like to go through the above mentioned steps just to have have a kind of flexible (modifiable) variable)?
What are some general ways to avoid this practice? Small examples will be greatly appreciated.
P.S. I just started learning Prolog. I do have programming experience in languages like C.
Edited for further clarification
A bad example (in win-prolog) of what I want to say is given below:
:- dynamic(value/1).
:- assert(value(0)).
adds :-
value(X),
NewX is X + 4,
retractall(value(_)),
assert(value(NewX)).
mults :-
value(Y),
NewY is Y * 2,
retractall(value(_)),
assert(value(NewY)).
start :-
retractall(value(_)),
assert(value(3)),
adds,
mults,
value(Q),
write(Q).
Then we can query like:
?- start.
Here, it is very trivial, but in real program and application, the above shown method of global variable becomes unavoidable. Sometimes the list given above like assert(value(0))... grows very long with many more assert predicates for defining more variables. This is done to make communication of the values between different functions possible and to store states of variables during the runtime of program.
Finally, I'd like to know one more thing:
When does the practice mentioned above become unavoidable in spite of various solutions suggested by you to avoid it?
The general way to avoid this is to think in terms of relations between states of your computations: You use one argument to hold the state that is relevant to your program before a calculation, and a second argument that describes the state after some calculation. For example, to describe a sequence of arithmetic operations on a value V0, you can use:
state0_state(V0, V) :-
operation1_result(V0, V1),
operation2_result(V1, V2),
operation3_result(V2, V).
Notice how the state (in your case: the arithmetic value) is threaded through the predicates. The naming convention V0 -> V1 -> ... -> V scales easily to any number of operations and helps to keep in mind that V0 is the initial value, and V is the value after the various operations have been applied. Each predicate that needs to access or modify the state will have an argument that allows you to pass it the state.
A huge advantage of threading the state through like this is that you can easily reason about each operation in isolation: You can test it, debug it, analyze it with other tools etc., without having to set up any implicit global state. As another huge benefit, you can then use your programs in more directions provided you are using sufficiently general predicates. For example, you can ask: Which initial values lead to a given outcome?
?- state0_state(V0, given_outcome).
This is of course not readily possible when using the imperative style. You should therefore use constraints instead of is/2, because is/2 only works in one direction. Constraints are much easier to use and a more general modern alternative to low-level arithmetic.
The dynamic database is also slower than threading states through in variables, because it performs indexing etc. on each assertz/1.
1 - it's bad practice because destroys the declarative model that (pure) Prolog programs exhibit.
Then the programmer must think in procedural terms, and the procedural model of Prolog is rather complicate and difficult to follow.
Specifically, we must be able to decide about the validity of asserted knowledge while the programs backtracks, i.e. follow alternative paths to those already tried, that (maybe) caused the assertions.
2 - We need additional variables to keep the state. A practical, maybe not very intuitive way, is using grammar rules (a DCG) instead of plain predicates. Grammar rules are translated adding two list arguments, normally hidden, and we can use those arguments to pass around the state implicitly, and reference/change it only where needed.
A really interesting introduction is here: DCGs in Prolog by Markus Triska. Look for Implicitly passing states around: you'll find this enlighting small example:
num_leaves(nil), [N1] --> [N0], { N1 is N0 + 1 }.
num_leaves(node(_,Left,Right)) -->
num_leaves(Left),
num_leaves(Right).
More generally, and for further practical examples, see Thinking in States, from the same author.
edit: generally, assert/retract are required only if you need to change the database, or keep track of computation result along backtracking. A simple example from my (very) old Prolog interpreter:
findall_p(X,G,_):-
asserta(found('$mark')),
call(G),
asserta(found(X)),
fail.
findall_p(_,_,N) :-
collect_found([],N),
!.
collect_found(S,L) :-
getnext(X),
!,
collect_found([X|S],L).
collect_found(L,L).
getnext(X) :-
retract(found(X)),
!,
X \= '$mark'.
findall/3 can be seen as the basic all solutions predicate. That code should be the very same from Clockins-Mellish textbook - Programming in Prolog. I used it while testing the 'real' findall/3 I implemented. You can see that it's not 'reentrant', because of the '$mark' aliased.