How to determine the outcome of queries for constraint logic programming - prolog

I am doing some revision for constraint logic programming and wanted to know how I can read the following queries in order to predicate their results correctly.
Basically there is a question which asks whether or not the answer provided by the following query is correct or not.
So this is the question
Consider the following queries and answers. Some answers coincide
with what SWI-Prolog would infer whereas others are erroneous.
Indicate which answers are genuine and which ones are fake (no
explanation is required).
(i) ?- [X, Y, Z] ins 0 .. 4, X #= Y + 1.
X in 1..4, Y in 0..3, Z in 0..4.
(ii) ?- [X, Y, Z] ins 0 .. 4, X #= Y + Z.
X in 0..4, Y in 0..2, Z in 0..2.
(iii) ?- [X, Y, Z] ins 0 .. 4, X #= Z - Y.
X in 0..4, Y in 0..4, Z in 0..4.
(iv) ?- [X, Y, Z] ins 0 .. 4, X #= Y * Y, Z #= -Y.
Y = 0, Z = 0.
My question is what is the best way to read the query in order to determine whether the answer is correct or not.

Several steps:
Is the shown answer a syntactically valid Prolog goal? If not, then the answer is definitely fake, because the actual toplevel only emits syntactically valid residual goals.
Moving on: Are there any solutions of the original query that are precluded by the shown residual goals? If yes (= incompleteness), then the answer is fake, because the actual toplevel only emits residual goals that are semantically equivalent to the original query.
Conversely, do the residual goals admit a solution that the initial query does not? If yes (= overly general), then the answer is fake. Exercise: Why?
In your case, the shown answer is a syntactically valid conjunction, so it is definitely a candidate for a correct solution. However, the answer admits solutions (exercise: which?) that the original query does not, and so the answer is not correct.

Related

Why does returning false? [duplicate]

I implemented the following power program in Prolog:
puissance(_,0,1).
puissance(X,N,P) :- N>0,A is N-1, puissance(X,A,Z), P is Z*X.
The code does what is supposed to do, but after the right answer it prints "false.". I don't understand why. I am using swi-prolog.
Can do like this instead:
puissance(X,N,P) :-
( N > 0 ->
A is N-1,
puissance(X,A,Z),
P is Z*X
; P = 1 ).
Then it will just print one answer.
(Your code leaves a `choice point' at every recursive call, because you have two disjuncts and no cut. Using if-then-else or a cut somewhere removes those. Then it depends on the interpreter what happens. Sicstus still asks if you want ((to try to find)) more answers.)
Semantic differences
Currently, there are 3 different versions of puissance/3, and I would like to show a significant semantic difference between some of them.
As a test case, I consider the query:
?- puissance(X, Y, Z), false.
What does this query mean? Declaratively, it is clearly equivalent to false. This query is very interesting nevertheless, because it terminates iff puissance/3 terminates universally.
Now, let us try the query on the different variants of the program:
Original definition (from the question):
?- puissance(X, Y, Z), false.
ERROR: puissance/3: Arguments are not sufficiently instantiated
Accepted answer:
?- puissance(X, Y, Z), false.
false.
Other answer:
?- puissance(X, Y, Z), false.
ERROR: puissance/3: Arguments are not sufficiently instantiated
Obviously, the solution shown in the accepted answer yields a different result, and is worth considering further.
Here is the program again:
puissance(_,0,1) :- !.
puissance(X,N,P) :- N>0,A is N-1, puissance(X,A,Z), P is Z*X.
Let us ask something simple first: Which solutions are there at all? This is called the most general query, because its arguments are all fresh variables:
?- puissance(X, Y, Z).
Y = 0,
Z = 1.
The program answers: There is only a single solution: Y=0, Z=1.
That's incorrect (to see this, try the query ?- puissance(0, 1, _) which succeeds, contrary to the same program claiming that Y can only be 0), and a significant difference from the program shown in the question. For comparison, the original program yields:
?- puissance(X, Y, Z).
Y = 0,
Z = 1 ;
ERROR: puissance/3: Arguments are not sufficiently instantiated
That's OK: On backtracking, the program throws an instantiation error to indicate that no further reasoning is possible at this point. Critically though, it does not simply fail!
Improving determinism
So, let us stick to the original program, and consider the query:
?- puissance(1, 1, Z).
Z = 1 ;
false.
We would like to get rid of false, which occurs because the program is not deterministic.
One way to solve this is to use zcompare/3 from library(clpfd). This lets you reify the comparison, and makes the result available for indexing while retaining the predicate's generality.
Here is one possible solution:
puissance(X, N, P) :-
zcompare(C, 0, N),
puissance_(C, X, N, P).
puissance_(=, _, 0, 1).
puissance_(<, X, N, P) :-
A #= N-1,
puissance(X, A, Z),
P #= Z*X.
With this version, we get:
?- puissance(1, 1, Z).
Z = 1.
This is now deterministic, as intended.
Now, let us consider the test case from above with this version:
?- puissance(X, Y, Z), false.
nontermination
Aha! So this query neither throws an instantiation error nor terminates, and is therefore different from all the versions that have hitherto been posted.
Let us consider the most general query with this program:
?- puissance(X, Y, Z).
Y = 0,
Z = 1 ;
X = Z,
Y = 1,
Z in inf..sup ;
Y = 2,
X^2#=Z,
Z in 0..sup ;
Y = 3,
_G3136*X#=Z,
X^2#=_G3136,
_G3136 in 0..sup ;
etc.
Aha! So we get a symbolic representation of all integers that satisfy this relation.
That's pretty cool, and I therefore recommend you use CLP(FD) constraints when reasoning over integers in Prolog. This will make your programs more general and also lets you improve their efficiency more easily.
You can add a cut operator (i.e. !) to your solution, meaning prolog should not attempt to backtrack and find any more solutions after the first successful unification that has reached that point. (i.e. you're pruning the solution tree).
puissance(_,0,1) :- !.
puissance(X,N,P) :- N>0,A is N-1, puissance(X,A,Z), P is Z*X.
Layman's Explanation:
The reason prolog attempts to see if there are any more solutions, is this:
At the last call to puissance in your recursion, the first puissance clause succeeds since P=1, and you travel all the way back to the top call to perform unification with P with the eventual value that results from that choice.
However, for that last call to puissance, Prolog didn't have a chance to check whether the second puissance clause would also be satisfiable and potentially lead to a different solution, therefore unless you tell it not to check for further solutions (by using a cut on the first clause after it has been successful), it is obligated to go back to that point, and check the second clause too.
Once it does, it sees that the second clause cannot be satisfied because N = 0, and therefore that particular attempt fails.
So the "false" effectively means that prolog checked for other choice points too and couldn't unify P in any other way that would satisfy them, i.e. there are no more valid unifications for P.
And the fact that you're given the choice to look for other solutions in the first place, exactly means that there are still other routes with potentially satisfiable clauses remaining that have not been explored yet.

Prolog program returns false

I implemented the following power program in Prolog:
puissance(_,0,1).
puissance(X,N,P) :- N>0,A is N-1, puissance(X,A,Z), P is Z*X.
The code does what is supposed to do, but after the right answer it prints "false.". I don't understand why. I am using swi-prolog.
Can do like this instead:
puissance(X,N,P) :-
( N > 0 ->
A is N-1,
puissance(X,A,Z),
P is Z*X
; P = 1 ).
Then it will just print one answer.
(Your code leaves a `choice point' at every recursive call, because you have two disjuncts and no cut. Using if-then-else or a cut somewhere removes those. Then it depends on the interpreter what happens. Sicstus still asks if you want ((to try to find)) more answers.)
Semantic differences
Currently, there are 3 different versions of puissance/3, and I would like to show a significant semantic difference between some of them.
As a test case, I consider the query:
?- puissance(X, Y, Z), false.
What does this query mean? Declaratively, it is clearly equivalent to false. This query is very interesting nevertheless, because it terminates iff puissance/3 terminates universally.
Now, let us try the query on the different variants of the program:
Original definition (from the question):
?- puissance(X, Y, Z), false.
ERROR: puissance/3: Arguments are not sufficiently instantiated
Accepted answer:
?- puissance(X, Y, Z), false.
false.
Other answer:
?- puissance(X, Y, Z), false.
ERROR: puissance/3: Arguments are not sufficiently instantiated
Obviously, the solution shown in the accepted answer yields a different result, and is worth considering further.
Here is the program again:
puissance(_,0,1) :- !.
puissance(X,N,P) :- N>0,A is N-1, puissance(X,A,Z), P is Z*X.
Let us ask something simple first: Which solutions are there at all? This is called the most general query, because its arguments are all fresh variables:
?- puissance(X, Y, Z).
Y = 0,
Z = 1.
The program answers: There is only a single solution: Y=0, Z=1.
That's incorrect (to see this, try the query ?- puissance(0, 1, _) which succeeds, contrary to the same program claiming that Y can only be 0), and a significant difference from the program shown in the question. For comparison, the original program yields:
?- puissance(X, Y, Z).
Y = 0,
Z = 1 ;
ERROR: puissance/3: Arguments are not sufficiently instantiated
That's OK: On backtracking, the program throws an instantiation error to indicate that no further reasoning is possible at this point. Critically though, it does not simply fail!
Improving determinism
So, let us stick to the original program, and consider the query:
?- puissance(1, 1, Z).
Z = 1 ;
false.
We would like to get rid of false, which occurs because the program is not deterministic.
One way to solve this is to use zcompare/3 from library(clpfd). This lets you reify the comparison, and makes the result available for indexing while retaining the predicate's generality.
Here is one possible solution:
puissance(X, N, P) :-
zcompare(C, 0, N),
puissance_(C, X, N, P).
puissance_(=, _, 0, 1).
puissance_(<, X, N, P) :-
A #= N-1,
puissance(X, A, Z),
P #= Z*X.
With this version, we get:
?- puissance(1, 1, Z).
Z = 1.
This is now deterministic, as intended.
Now, let us consider the test case from above with this version:
?- puissance(X, Y, Z), false.
nontermination
Aha! So this query neither throws an instantiation error nor terminates, and is therefore different from all the versions that have hitherto been posted.
Let us consider the most general query with this program:
?- puissance(X, Y, Z).
Y = 0,
Z = 1 ;
X = Z,
Y = 1,
Z in inf..sup ;
Y = 2,
X^2#=Z,
Z in 0..sup ;
Y = 3,
_G3136*X#=Z,
X^2#=_G3136,
_G3136 in 0..sup ;
etc.
Aha! So we get a symbolic representation of all integers that satisfy this relation.
That's pretty cool, and I therefore recommend you use CLP(FD) constraints when reasoning over integers in Prolog. This will make your programs more general and also lets you improve their efficiency more easily.
You can add a cut operator (i.e. !) to your solution, meaning prolog should not attempt to backtrack and find any more solutions after the first successful unification that has reached that point. (i.e. you're pruning the solution tree).
puissance(_,0,1) :- !.
puissance(X,N,P) :- N>0,A is N-1, puissance(X,A,Z), P is Z*X.
Layman's Explanation:
The reason prolog attempts to see if there are any more solutions, is this:
At the last call to puissance in your recursion, the first puissance clause succeeds since P=1, and you travel all the way back to the top call to perform unification with P with the eventual value that results from that choice.
However, for that last call to puissance, Prolog didn't have a chance to check whether the second puissance clause would also be satisfiable and potentially lead to a different solution, therefore unless you tell it not to check for further solutions (by using a cut on the first clause after it has been successful), it is obligated to go back to that point, and check the second clause too.
Once it does, it sees that the second clause cannot be satisfied because N = 0, and therefore that particular attempt fails.
So the "false" effectively means that prolog checked for other choice points too and couldn't unify P in any other way that would satisfy them, i.e. there are no more valid unifications for P.
And the fact that you're given the choice to look for other solutions in the first place, exactly means that there are still other routes with potentially satisfiable clauses remaining that have not been explored yet.

swi-prolog abs operator not working in clpfd module

I am doing some toy tests with the CLPFD library in swi-prolog.
Does anybody know why the program below does not work?
start(X,Y):-
Vars = [X,Y],
Vars ins 1..3,
abs(X-Y) #>= 2,
X #>= Y,
nl,
write([X,Y]), nl.
The expected answer for start(X,Y) would be X=3 and Y=1. However, swi-prolog indicates me multiple answers. The program works properly if I replace
abs(X-Y) #>= 2
by
X-Y #>= 2
My question is whether I am using the abs operator in the right way.
First of all, constraints and side-effects do not flock together. Instead, simply stick to the pure part of your program:
start(X,Y):-
Vars = [X,Y],
Vars ins 1..3,
abs(X-Y) #>= 2,
X #>= Y.
And now, query your relation:
?- start(X,Y).
X in 1..3, X#>=Y, abs(X-Y)#>=2, Y in 1..3.
The answer is a conditional one:
Yes, there are solutions for X and Y provided all these conditions hold.
To get actual values, you have to eliminate all these conditions. You have several options:
In this case, you can use labeling/2:
?- start(X,Y), labeling([], [X,Y]).
X = 3, Y = 1.
So there is exactly one solution. The clpfd-solver alone was not powerful enough to come to this conclusion, it needed some extra help.
Even better would be to use contracting/1:
?- start(X,Y), clpfd:contracting([X,Y]).
X = 3, Y = 1.
In contrast to labeling, contracting tries to reduce the size of the domain without (visible) search. This makes the solver a bit stronger.
Reasons why the solver is not powerful enough
in the very general case solving such arithmetic problems is undecidable.
in more specific cases the algorithms would be extremely costly. In fact, there is more than one diophant in the room.
even simpler algorithms are very costly in terms of both implementation effort and runtime.
for many situations, the solver boils down to maintaining consistencies within one constraint1. So the only way to "communicate" between different constraints are the domains of variables.
In your case, the abs-constraint admits more solutions!
?- [X,Y]ins 1..3, abs(X-Y)#>=2, labeling([],[X,Y]).
X = 1, Y = 3
; X = 3, Y = 1.
?- [X,Y]ins 1..3, X-Y#>=2, labeling([],[X,Y]).
X = 3, Y = 1.
What you expect is that the extra constraint X #>= Y would help. Alas, the concrete consistency mechanisms are too weak. And not even X #> Y helps:
?- [X,Y]ins 1..3, abs(X-Y)#>=2, X#>Y.
X in 2..3, Y#=<X+ -1, abs(X-Y)#>=2, Y in 1..2.
However, if you switch from SWI to SICStus, things are a bit different:
| ?- assert(clpfd:full_answer).
| ?- X in 1..3, Y in 1..3, abs(X-Y)#>=2.
Y+_A#=X, X in 1..3, Y in 1..3, _A in{-2}\/{2}.
| ?- X in 1..3, Y in 1..3, abs(X-Y)#>=2, X#>Y.
X = 3, Y = 1.
Please note how abs is resolved!
And using SICStus with library(clpz) has the same strength:
| ?- X in 1..3, Y in 1..3, abs(X-Y)#>=2, X#>Y.
X = 3, Y = 1.
1 Note that I avoid to use the notion of local consistency as opposed to global consistency, since quite often also global consistency only refers to consistency within one "global" constraint.

Prolog: How can I implement the sum of squares of two largest numbers out of three?

Exercise 1.3 of the book Structure and Interpretation of Computer Programs asks the following:
Define a procedure that takes three numbers as arguments and returns the sum of the squares of the two larger numbers.
I'm learning Prolog. Here's the function I tried to implement:
square(X, Y) :- Y is X * X.
squareTwoLargest(X, Y, Z, R) :-
R is square(L1) + square(L2), L1 = max(X, Y), L2 = max(min(X, Y), Z).
However, when I run it, it gives the following error: ERROR: is/2: Arguments are not sufficiently instantiated. I think I'm not only not getting Prolog's syntax, but I'm also not getting the logic programming paradigm yet. So, how could I implement this function in good logic programming style?
To get the two largest numbers out of three (V1, V2, and V3) you can proceed as follows: Sort the list [V1,V2,V3] and take the last two list items [_,X,Y], square and sum them.
:- use_module(library(lists)).
:- use_module(library(clpfd)).
squareTwoLargest(V1,V2,V3, R) :-
Zs = [_,X,Y],
chain(Zs, #=<),
permutation([V1,V2,V3],Zs),
R #= X*X + Y*Y.
Sample query:
?- squareTwoLargest(20,30,10, R).
R = 1300
Better implementation
Above code is based on "permutation sort", which makes it inefficient in more than one way.
The goal squareTwoLargest(X,Y,Z, R) succeeds multiple times and gives redundant answers, if two or more of X, Y, and Z are equal. This is shown by the following two queries:
?- squareTwoLargest(0,10,10, R).
R = 200 ;
R = 200 ;
false.
?- squareTwoLargest(10,10,10, R).
R = 200 ;
R = 200 ;
R = 200 ;
R = 200 ;
R = 200 ;
R = 200 ;
false.
We can eliminate the redundant answers by using a sorting network of size 3. For details, look at this answer to the question
ordering lists with constraint logic programming.
list_sorted__SN3([A0,A1,A2], [D0,D1,C2]) :-
B1 #= min(A1,A2), B2 #= max(A1,A2),
C0 #= min(A0,B2), C2 #= max(A0,B2),
D0 #= min(C0,B1), D1 #= max(C0,B1).
squareTwoLargest__SN(V1,V2,V3, R) :-
list_sorted__SN3([V1,V2,V3],[_,X,Y]),
R #= X*X + Y*Y.
Consider the following queries:
?- squareTwoLargest__SN(20,30,10, R).
R = 1300. % works like it did before
?- squareTwoLargest__SN(20,20,10, R).
R = 800. % succeeds deterministically
?- squareTwoLargest__SN(20,20,20, R).
R = 800. % succeeds deterministically
Note that all redundant answers of the corner cases shown above have been eliminated.
Unfortunately, max function you are using, is built-in arithmetic function and does not behave as a predicate, this may trick you into thinking that you will write your predicates in the same way.
In Prolog, what you will be writing is predicates. Predicate does not return any value, it just holds or does not hold (you can think of it as if it returned true or false). Your predicate square is a good example, what it square(X,Y) really means is 'Y is square of X'. If you ask Prolog console square(4, 16)., it will tell you true. If you ask square(4, 44), it will tell you false. So how do you find out square root of some number? You ask Prolog a question with free (unknown) variable square(4,R)., then Prolog will tell you that R=16. That is the important part of logical programming, you do not explain Prolog, how to calculate square, you only tell Prolog what square is in terms of logic and then you ask Prolog question and it will find answer by itself.
Soo what if you try instead of
R is square(L1) + square(L2)
something like
square(L2, L2SQUARED), square(L1, L1SQUARED), ...
which will give you square of L1 in L1SQUARED
However, L1 must not be free variable, Prolog must be able to deduce some value for it based on some other predicates (...), so that it can answer to square(L1, L1SQUARED). Imagine question square(SOMETHING1, SOMETHING2), where both arguments are unknown, what will the answer be? There is infinite number of correct answers, for example [2, 4] or [3, 9] etc.
Note: yes, it can be onliner with arithmetics, but if you want to learn logical programming, try more 'logical programming' like approach. In some flavours of Prolog, you do not get arithmetics and they are still useful...
my bet, using the 'if-then-else' construct.
squareTwoLargest(X, Y, Z, R) :-
( X > Y -> A = X, B = Y ; A = Y, B = X ),
R is A + max(B, Z).
Two temp variables are needed.

Prolog Beginner: How to unify with arithmetic comparison operators or how to get a set var to range of values

I am new to Prolog. I need to write an integer adder that will add numbers between 0-9 to other numbers 0-9 and produce a solution 0-18. This is what I want to do:
% pseudo code
add(in1, in2, out) :-
in1 < 10,
in2 < 10,
out < 18.
I would like to be able to call it like this:
To check if it is a valid addition:
?- add(1,2,3).
true.
?- add(1,2,4).
false.
With one missing variable:
?- add(X,2,3).
X = 1.
?- add(1,4,X).
X = 5.
With multiple missing variables:
?- add(X,Y,Z).
% Some output that would make sense. Some examples could be:
X=1, Y=1, Z=2 ;
X=2, Y=1, Z=3 ......
I realize that this is probably a pretty simplistic question and it is probably very straightforward. However, according to the Prolog tutorial I am using:
"Unlike unification Arithmetic Comparison Operators operators cannot be used to give values to a variable. The can only be evaluated when every term on each side have been instantiated."
All modern Prolog systems provide finite domain constraints, which are true relations that can (in contrast to more low-level arithmetic predicates like is/2 and >/2) be used in all directions. In SWI-Prolog:
:- use_module(library(clpfd)).
plus(X, Y, Z) :-
[X,Y] ins 0..9,
X + Y #= Z.
Results for your examples:
?- plus(1,2,3).
true.
?- plus(1,2,4).
false.
?- plus(X,2,3).
X = 1.
?- plus(1,4,X).
X = 5.
?- plus(X,Y,Z).
X in 0..9,
X+Y#=Z,
Y in 0..9,
Z in 0..18.
Since the predicate can be used in all directions, it does no longer make sense to call it "add/3", as that would imply a direction, but the predicate truly describes when the relation holds and is thus more general.
What about this?:
add(X,Y,Z) :-
Z is X + Y,
X < 10,
Y < 10,
Z < 19.
Problem: this works nicely for queries of the form add(1,1,X) because Z's instantiated before the < calls, but fails when you ask add(X,1,2). You could use var/1 to distinguish the kind of query (var/1 tells you whether a variable's uninstantiated or not), but that sounds like a lot of pain.
Solution:
lessThanTen(9).
lessThanTen(8).
lessThanTen(7).
lessThanTen(6).
lessThanTen(5).
lessThanTen(4).
lessThanTen(3).
lessThanTen(2).
lessThanTen(1).
lessThanTen(0).
addSimple(Add1,Add2,Sol) :-
lessThanTen(Add1),
lessThanTen(Add2),
Sol is Add1+Add2.

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