When attempting to solve logic problems on a computer, it is usual to first convert them to CNF, because the best solving algorithms expect CNF as input.
For propositional logic, the textbook rules for this conversion are simple, but if you apply them as is, the result is one of the very rare cases where a program encounters double exponential resource consumption without being specifically constructed to do so:
a <=> (b <=> (c <=> ...))
with N variables, generates 2^2^N clauses, one exponential blowup in the conversion of equivalence to AND/OR, and another in the distribution of OR into AND.
The solution to this is to rename subterms. If we rewrite the above as something like
r <=> (c <=> ...)
a <=> (b <=> r)
where r
is a fresh symbol that is being defined to be equal to a subterm - in general, we may need O(N) such symbols - the exponential blowups can be avoided.
Unfortunately, this runs into a problem when we try to extend it to first-order logic. Using TPTP notation where ?
means 'there exists' and variables begin with capital letters, consider
a <=> ?[X]:p(X)
Admittedly this case is simple enough that there is no actual need to rename the subterm, but it's necessary to use a simple case for illustration, so suppose we are using an algorithm that just automatically renames arguments of the equivalence operator; the point generalizes to more complex cases.
If we try the above trick and rename the ?
subterm, we get
r <=> ?[X]:p(X)
Existential variables are converted to Skolem symbols, so that ends up as
r <=> p(s)
The original formula then expands to
(~a | r) & (a | ~r)
Which is by construction equivalent to
(~a | p(s)) & (a | ~p(s))
But this is not correct! Suppose we had not done the renaming, but just expanded the original formula as it was, we would get
(~a | ?[X]:p(X)) & (a | ~?[X]:p(X))
(~a | ?[X]:p(X)) & (a | ![X]:~p(X))
(~a | p(s)) & (a | ~p(X))
which is critically different from the version we got with the renaming.
The problem is that equivalence needs both the positive and negative versions of each argument, but applying negation to terms that contain universal or existential quantifiers, structurally changes those terms; you cannot just encapsulate them in a definition, then apply the negation to the defined symbol.
The upshot of this is that when you have equivalence and the arguments may contain such quantifiers, you actually need to recur through each argument twice, once for the positive version, once for the negative. This suffices to bring back the existential blowup we hoped to avoid by doing the renaming. As far as I can see, this problem is not caused by the way a particular algorithm works, but by the nature of the task.
So my question:
Given an input formula that may contain arbitrary nesting of equivalence and quantifiers, is there any algorithm that will correctly turn this to CNF with a polynomial rather than exponential number of clauses?