Is Datalog negation and the built-in predicate $ \neq $ similar?

Question

I was reading "Principles of Database & Knowledge-Base Systems, Vol. 1" by Jeffrey D. Ullman. There is a chapter about Datalog negation and as I was seeing the problems of negation I kept thinking that using the predicate $ \neq $ would solve those problems but then I see the following:

p(X) :- r(X) & ¬q(X).

q(X) :- r(X) & ¬p(X).

The problem is this has 2 minimal models and if I'm not mistaken so does this:

p(X) :- r(X) & q(Y) & X $ \neq $ Y.

q(X) :- r(X) & p(Y) & X $ \neq $ Y.

Is there an equivalence between these 2 operators? If so, did I miss it or is it not mentioned that it's unsafe to use $ \neq $ with recursion?

Answer 1

There was a misunderstanding in regards to the evaluation algorithm/minimal model.

The derivation of new values is atomic e.g.:

step 1:

• p = {}
• q = {}

step 2:

• p = r
• q = r

In step 2 p and q only see the value that each other had at step 1(the old value). I thought p and q would have access to the value of the current step and thus, the order of evaluation would produce different results.

To answer the question:

p(X) :- r(X) & q(Y) & X ≠ Y.

q(X) :- r(X) & p(Y) & X ≠ Y.

only has one minimal model: p = r and q = r.