Simple boolean expression testing - prolog

| ?- [user].
compiling user for byte code...
formula_0(P, Q):- (P; Q), \+ P.
user compiled, 2 lines read - 768 bytes written, 37208 ms
yes
| ?- formula_0(P, Q).
uncaught exception: error(instantiation_error,formula_0/2)
All I basically want to do is to ask is the set of expressions {P or Q, ~P} satisfiable?
But the error message is not helping here...
PS. The answer should be "yes", this formula is satisfied when P = false and Q = true.

The reason you get an instantiation error is that too little is known about P and Q to say anything about them at the time they are used as goals. You are right that when you ask for example:
?- G.
then G = true is a solution that makes the query succeed. But so is for example G = (a=a) because a=a is also true. Since it is not possible to enumerate all goals G that succeed, you get an instantiation error. But notice for example that when you explicitly give a binding, you get the result you expect:
?- G = true, G.
G = true.
So, you should provide a set of values you are interested in:
?- maplist(boolean, [P,Q]), formula(P, Q).
and define for example:
boolean(true).
boolean(false).
to obtain concrete solutions. Or use constraints, which let you constrain the domain of variables before using them.
EDIT: Since there was some discussion about this, I go into more detail. The main question that arose is: Why does the query
?- Q.
not succeed with the sole solution
Q = true.
since obviously, true succeeds and is thus a valid solution? Answer: There are other possible answers as well, since true is not the only goal that succeeds. For example, the conjunction (true,true) succeeds as well. Suppose now that Q = true were the only solution to the above query, then it would be the case that:
?- Q, Q = (true, true).
fails (since dif(true, (true,true)) is itself true), but simply exchanging the goals like
?- Q = (true,true), Q.
succeeds because otherwise ?- true, true would also have to fail and that cannot be the case. This would violate commutativity of conjunction already for the most basic predicate (unification).
Note that while true and (true,true) both succeed when executed as goals, they are obviously different terms and cannot replace each other in general. Similarly, the term append([], [], []) is different from the term true, although both succeed when executed as goals. You therefore get an instantiation error, since too little is known about Q in a query like ?- Q. to give useful results.

Use clpb for constraint logic programming over Booleans.
:- use_module(library(clpb)).
Sample query:
?- sat((P+Q) * ~P).
P = 0, Q = 1. % succeeds deterministically

Gnu Prolog supports the 'naked variable' call, a syntactic feature that allows to write code like you show in formula_0/2. But when it come to executing it, variables must be bound !
| ?- P.
uncaught exception: error(instantiation_error,top_level/0)
| ?- P=write(1), P.
1
P = write(1)
then just use callables:
| ?- formula_0(fail,true).
yes

Related

CLPFD ins operator yields not sufficiently instantiated error

So, my goal is to make a map colourer in Prolog. Here's the map I'm using:
And this are my colouring constraints:
colouring([A,B,C,D,E,F]) :-
maplist( #\=(A), [B,C,D,E] ),
maplist( #\=(B), [C,D,F]),
C #\= D,
maplist( #\=(D), [E,F]),
E #\= F.
Where [A,B,C,D,E,F] is a list of numbers(colors) from 1 to n.
So I want my solver to, given a List of 6 colors and a natural number N, determine the colors and N constraints both ways, in a way that even the most general query could yield results:
regions_ncolors(L,N) :- colouring(L), L ins 1..N, label(L).
Where the most general query is regions_ncolors(L,N).
However, the operator ins doesn't seem to accept a variable N, it instead yields an argument not sufficiently instantiated error. I've tried using this solution instead:
int_cset_(N,Acc,Acc) :- N #= 0.
int_cset_(N,Acc,Cs) :- N_1 #= N-1, int_cset_(N_1,[N|Acc],Cs).
int_cset(N,Cs) :- int_cset_(N,[],Cs).
% most general solver
regions_ncolors(L,N) :- colouring(L), int_cset(N,Cs), subset(L,Cs), label(L).
Where the arguments in int_cset(N,Cs) is a natural number(N) and the counting set Sn = {1,2,...,N}
But this solution is buggy as regions_ncolors(L,N). only returns the same(one) solution for all N, and when I try to add a constraint to N, it goes in an infinite loop.
So what can I do to make the most general query work both ways(for not-instantiated variables)?
Thanks in advance!
Btw, I added a swi-prolog tag in my last post although it was removed by moderation. I don't know if this question is specific to swi-prolog which is why I'm keeping the tag, just in case :)
Your colouring is too specific, you encode the topology of your map into it. Not a problem as is, but it defeats of the purpose of then having a "most general query" solution for just any list.
If you want to avoid the problem of having a free variable instead of a list, you could first instantiate the list with length/2. Compare:
?- L ins 1..3.
ERROR: Arguments are not sufficiently instantiated
ERROR: In:
ERROR: [16] throw(error(instantiation_error,_86828))
ERROR: [10] clpfd:(_86858 ins 1..3) ...
Is that the same problem as you see?
If you first make a list and a corresponding set:
?- length(L, N), L ins 1..N.
L = [],
N = 0 ;
L = [1],
N = 1 ;
L = [_A, _B],
N = 2,
_A in 1..2,
_B in 1..2 ;
L = [_A, _B, _C],
N = 3,
_A in 1..3,
_B in 1..3,
_C in 1..3 .
If you use length/2 like this you will enumerate the possible lists and integer sets completely outside of the CLP(FD) labeling. You can then add more constraints on the variables on the list and if necessary, use labeling.
Does that help you get any further with your problem? I am not sure how it helps for the colouring problem. You would need a different representation of the map topology so that you don't have to manually define it within a predicate like your colouring/1 you have in your question.
There are several issues in your program.
subset/2 is impure
SWI's (by default) built-in predicate subset/2 is not the pure relation you are hoping for. Instead, it expects that both arguments are already sufficiently instantiated. And if not, it takes a guess and sticks to it:
?- colouring(L), subset(L,[1,2,3,4,5]).
L = [1,2,3,4,2,1].
?- colouring(L), subset(L,[1,2,3,4,5]), L = [2|_].
false.
?- L = [2|_], colouring(L), subset(L,[1,2,3,4,5]), L = [2|_].
L = [2,1,3,4,1,2].
With a pure definition it is impossible that adding a further goal as L = [2|_] in the third query makes a failing query succeed.
In general it is a good idea to not interfere with labeling/2 except for the order of variables and the options argument. The internal implementation is often much faster than manual instantiations.
Also, your map is far too simple to expose subset/2s weakness. Not sure what the minimal failing graph is, but here is one such example from
R. Janczewski et al. The smallest hard-to-color graph for algorithm DSATUR, Discrete Mathematics 236 (2001) p.164.
colouring_m13([K1,K2,K3,K6,K5,K7,K4]):-
maplist(#\=(K1), [K2,K3,K4,K7]),
maplist(#\=(K2), [K3,K5,K6]),
maplist(#\=(K3), [K4,K5]),
maplist(#\=(K4), [K5,K7]),
maplist(#\=(K5), [K6,K7]),
maplist(#\=(K6), [K7]).
?- colouring_m13(L), subset(L,[1,2,3,4]).
false. % incomplete
?- L = [3|_], colouring_m13(L), subset(L,[1,2,3,4]).
L = [3,1,2,2,3,1,4].
int_cset/2 never terminates
... (except for some error cases like int_cset(non_integer, _).). As an example consider:
?- int_cset(1,Cs).
Cs = [1]
; loops.
And don't get fooled by the fact that an actual solution was found! It still does not terminate.
#Luis: But how come? I'm getting baffled by this, the same thing is happening on ...
To see this, you need the notion of a failure-slice which helps to identify the responsible part in your program. With some falsework consisting of goals false the responsible part is exposed.
All unnecessary parts have been removed by false. What remains has to be changed somehow.
int_cset_(N,Acc,Acc) :- false, N #= 0.
int_cset_(N,Acc,Cs) :- N1 #= N-1, int_cset_(N1,[N|Acc],Cs), false.
int_cset(N,Cs) :- int_cset_(N,[],Cs), false.
?- int_cset(1, Cs), false.
loops.
Adding the redundant goal N1 #> 0
will avoid unnecessary non-termination.
This alone will not solve your problem since if N is not given, you will still encounter non-termination due to the following failure slice:
regions_ncolors(L,N) :-
colouring(L),
int_cset(N,Cs), false,
subset(L,Cs),
label(L).
In int_cset(N,Cs), Cs occurs for the first time and thus cannot influence termination (there is another reason too, its definition would ignore it as well..) and therefore only N has a chance to induce termination.
The actual solution has been already suggested by #TA_intern using length/2 which liberates one of such mode-infested chores.

Prolog order of clauses causes pathfinding to fail

I am developing a path finding algorithm in Prolog, giving all nodes accessible by a path from a starting node. To avoid duplicate paths, visited nodes are kept in a list.
Nodes and neighbors are defined as below:
node(a).
node(b).
node(c).
node(d).
node(e).
edge(a,b).
edge(b,c).
edge(c,d).
edge(b,d).
neighbor(X,Y) :- edge(X,Y).
neighbor(X,Y) :- edge(Y,X).
The original algorithm below works fine:
path2(X,Y) :-
pathHelper(X,Y,[X]).
pathHelper(X,Y,L) :-
neighbor(X,Y),
\+ member(Y,L).
pathHelper(X,Y,H) :-
neighbor(X,Z),
\+ member(Z,H),
pathHelper(Z,Y,[Z|H]).
This works fine
[debug] ?- path2(a,X).
X = b ;
X = c ;
X = d ;
X = d ;
X = c ;
false.
however, when changing the order of the two clauses in the second definition, such as below
pathHelper(X,Y,L) :-
\+ member(Y,L),
neighbor(X,Y).
When trying the same here, swipl returns the following:
[debug] ?- path2(a,X).
false.
The query doesn't work anymore, and only returns false. I have tried to understand this through the tracecommand, but still can't make sense of what exactly is wrong.
In other words, I am failing to understand why the order of neighbor(X,Y)and \+ member(Y,L)is crucial here. It makes sense to have neighbor(X,Y) first in terms of efficiency, but not in terms of correctness to me.
You are now encountering the not so clean-cut borders of pure Prolog and its illogical surroundings. Welcome to the real world.
Or rather, not welcome! Instead, let's try to improve your definition. The key problem is
\+ member(Y, [a]), Y = b.
which fails while
Y = b, \+ member(Y,[a]).
succeeds. There is no logic to justify this. It's just the operational mechanism of Prolog's built-in (\+)/1.
Happily, we can improve upon this. Enter non_member/2.
non_member(_X, []).
non_member(X, [E|Es]) :-
dif(X, E),
non_member(X, Es).
Now,
?- non_member(Y, [a]).
dif(Y,a).
Mark this answer, it says: Yes, Y is not an element of [a], provided Y is different from a. Think of the many solutions this answer includes, like Y = 42, or Y = b and infinitely many more such solutions that are not a. Infinitely many solutions captured in nine characters!
Now, both non_member(Y, [a]), Y = b and Y = b, non_member(Y, [a]) succeed. So exchanging them has only influence on runtime and space consumption. If we are at it, note that you check for non-memberness in two clauses. You can factor this out. For a generic solution to this, see closure/3. With it, you simply say: closure(neighbor, A,B).
Also consider the case where you have only edge(a,a). Your definition fails here for path2(a,X). But shouldn't this rather succeed?
And the name path2/2 is not that fitting, rather reserve this word for an actual path.
The doubt you have is related to how prolog handle negation. Prolog uses negation as failure. This means that, if prolog has to negate a goal g (indicate it with not(g)), it tries to prove g by executing it and then, if the g fails, not(g) (or \+ g, i.e. the negation of g) succeeds and viceversa.
Keep in mind also that, after the execution of not(g), if the goal has variables, they will not be instantiated. This because prolog should instantiate the variables with all the terms that makes g fail, and this is likely an infinite set (for example for a list, not(member(A,[a]) should instantiate the variable A with all the elements that are not in the list).
Let's see an example. Consider this simple program:
test:-
L = [a,b,c],
\+member(A,L),
writeln(A).
and run it with ?- trace, test. First of all you get a Singleton variable in \+: A warning for the reason i explained before, but let's ignore it and see what happens.
Call:test
Call:_5204=[a, b]
Exit:[a, b]=[a, b]
Call:lists:member(_5204, [a, b])
Exit:lists:member(a, [a, b]) % <-----
Fail:test
false
You see at the highlighted line that the variable A is instantiated to a and so member/2 succeeds and so \+ member(A,L) is false.
So, in your code, if you write pathHelper(X,Y,L) :- \+ member(Y,L), neighbor(X,Y)., this clause will always fail because Y is not sufficiently instantiated. If you swap the two terms, Y will be ground and so member/2 can fail (and \+member succeeds).

Setting types of unbound variables in Prolog

I'm trying to find a way to set the type of a variable before it has been bound to a value. Unfortunately, the integer/1 predicate cannot be used for this purpose:
%This goal fails if Int is an unbound variable.
get_first_int(Int,List) :-
integer(Int),member(Int,List),writeln(Int).
I wrote a predicate called is_int that attempts to check the type in advance, but it does not work as I expected. It allows the variable to be bound to an atom instead of an integer:
:- initialization(main).
%This prints 'a' instead of 1.
main :- get_first_int(Int,[a,b,c,1]),writeln(Int).
get_first_int(Int,List) :-
is_integer(Int),member(Int,List).
is_integer(A) :- integer(A);var(A).
Is it still possible to set the type of a variable that is not yet bound to a value?
In SWI-Prolog I have used when/2 for similar situations. I really don't know if it is a good idea, it definitely feels like a hack, but I guess it is good enough if you just want to say "this variable can only become X" where X is integer, or number, or atom and so on.
So:
will_be_integer(X) :- when(nonvar(X), integer(X)).
and then:
?- will_be_integer(X), member(X, [a,b,c,1]).
X = 1.
But I have the feeling that almost always you can figure out a less hacky way to achieve the same. For example, why not just write:
?- member(X, [a,b,c,1]), integer(X).
???
Specific constraints for integers
In addition to what Boris said, I have a recommendation for the particular case of integers: Consider using CLP(FD) constraints to express that a variable must be of type integer. To express only this quite general requirement, you can post a CLP(FD) constraint that necessarily holds for all integers.
For example:
?- X in inf..sup.
X in inf..sup.
From this point onwards, X can only be instantiated to an integer. Everything else will yield a type error.
For example:
?- X in inf..sup, X = 3.
X = 3.
?- X in inf..sup, X = a.
ERROR: Type error: `integer' expected, found `a' (an atom)
Declaratively, you can always replace a type error with silent failure, since no possible additional instantiation can make the program succeed if this error arises.
Thus, in case you prefer silent failure over this type error, you can obtain it with catch/3:
?- X in inf..sup, catch(X = a, error(type_error(integer,_),_), false).
false.
CLP(FD) constraints are tailor-made for integers, and let you express also further requirements for this specific domain in a convenient way.
Case-specific advice
Let us consider your specific example of get_first_int/2. First, let us rename it to list_first_integer/3 so that it is clear what each argument is, and also to indicate that we fully intend to use it in several directions, not just to "get", but also to test and ideally to generate lists and integers that are in this relation.
Second, note that this predicate is rather messy, since it impurely depends on the instantiation of the list and integer, a property which cannot be expressed in first-order logic but rather depends on something outside of this logic. If we accept this, then one quite straight-forward way to do what you primarily want is to write it as:
list_first_integer(Ls, I) :-
once((member(I0, Ls), integer(I0))),
I = I0.
This works as long as the list is sufficiently instantiated, which implicitly seems to be the case in your examples, but definitely need not be the case in general. For example, with fully instantiated lists, we get:
?- list_first_integer([a,b,c], I).
false.
?- list_first_integer([a,b,c,4], I).
I = 4.
?- list_first_integer([a,b,c,4], 3).
false.
In contrast, if the list is not sufficiently instantiated, then we have the following major problems:
?- list_first_integer(Ls, I).
nontermination
and further:
?- list_first_integer([X,Y,Z], I).
false.
even though a more specific instantiation succeeds:
?- X = 0, list_first_integer([X,Y,Z], I).
X = I, I = 0.
Core problem: Defaulty representation
The core problem is that you are reasoning here about defaulty terms: A list element that is still a variable may either be instantiated to an integer or to any other term in the future. A clean way out is to design your data representation to symbolically distinguish the possible cases. For example, let us use the wrapper i/1 to denote an integer, and o/1 to denote any other kind of term. With this representation, we can write:
list_first_integer([i(I)|_], I).
list_first_integer([o(_)|Ls], I) :-
list_first_integer(Ls, I).
Now, we get correct results:
?- list_first_integer([X,Y,Z], I).
X = i(I) ;
X = o(_12702),
Y = i(I) ;
X = o(_12702),
Y = o(_12706),
Z = i(I) ;
false.
?- X = i(0), list_first_integer([X,Y,Z], I).
X = i(0),
I = 0 ;
false.
And the other examples also still work, if we only use the clean data representation:
?- list_first_integer([o(a),o(b),o(c)], I).
false.
?- list_first_integer([o(a),o(b),o(c),i(4)], I).
I = 4 ;
false.
?- list_first_integer([o(a),o(b),o(c),i(4)], 3).
false.
The most general query now allows us to generate solutions:
?- list_first_integer(Ls, I).
Ls = [i(I)|_16880] ;
Ls = [o(_16884), i(I)|_16890] ;
Ls = [o(_16884), o(_16894), i(I)|_16900] ;
Ls = [o(_16884), o(_16894), o(_16904), i(I)|_16910] ;
etc.
The price you have to pay for this generality lies in these symbolic wrappers. As you seem to care about correctness and also about generality of your code, I consider this a bargain in comparison to more error prone defaulty approaches.
Synthesis
Note that CLP(FD) constraints can be naturally used together with a clean representation. For example, to benefit from more finely grained type errors as explained above, you can write:
list_first_integer([i(I)|_], I) :- I in inf..sup.
list_first_integer([o(_)|Ls], I) :-
list_first_integer(Ls, I).
Now, you get:
?- list_first_integer([i(a)], I).
ERROR: Type error: `integer' expected, found `a' (an atom)
Initially, you may be faced with a defaulty representation. In my experience, a good approach is to convert it to a clean representation as soon as you can, for the sake of the remainder of your program in which you can then distinguish all cases symbolically in such a way that no ambiguity remains.

Steadfastness: Definition and its relation to logical purity and termination

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..

prolog and translating propositional logic

My ultimate goal is to load a set of propositional formulas in to Prolog from a file in order to deduce some facts. Suppose I have the propositional formula:
p implies not(q).
In Prolog this would be:
not(q) :- p
Prolog does not seem to like the not operator in the head of the rule. I get the following error:
'$record_clause'/2: No permission to redefine built-in predicate `not/1'
Use :- redefine_system_predicate(+Head) if redefinition is intended
I know two ways to rewrite the general formula for p implies q. First, use the fact that the contrapositive is logically equivalent.
p implies q iff not(q) implies not(p)
Second, use the fact that p implies q is logically equivalent to not(p) or q (the truth tables are the same).
The first method leads me to my current problem. The second method is then just a conjunction or disjunction. You cannot write only conjunctions and disjunctions in Prolog as they are not facts or rules.
What is the best way around my problem so that I can express p implies not(q)?
Is it possible to write all propositional formulas in Prolog?
EDIT: Now I wish to connect my results with other propositional formulae. Suppose I have the following rule:
something :- formula(P, Q).
How does this connect? If I enter formula(false, true) (which evaluates to true) into the interpreter, this does not automatically make something true. Which is what I want.
p => ~q === ~p \/ ~q === ~( p /\ q )
So we can try to model this with a Prolog program,
formula(P,Q) :- P, Q, !, fail.
formula(_,_).
Or you can use the built-in \+ i.e. "not", to define it as formula(P,Q) :- \+( (P, Q) ).
This just checks the compliance of the passed values to the formula. If we combine this with domain generation first, we can "deduce" i.e. generate the compliant values:
13 ?- member(Q,[true, false]), formula(true, Q). %// true => ~Q, what is Q?
Q = false.
14 ?- member(Q,[true, false]), formula(false, Q). %// false => ~Q, what is Q?
Q = true ;
Q = false.
You are using the wrong tool. Try Answer Set Programming.

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