98,930 research outputs found
Resolution Trees with Lemmas: Resolution Refinements that Characterize DLL Algorithms with Clause Learning
Resolution refinements called w-resolution trees with lemmas (WRTL) and with
input lemmas (WRTI) are introduced. Dag-like resolution is equivalent to both
WRTL and WRTI when there is no regularity condition. For regular proofs, an
exponential separation between regular dag-like resolution and both regular
WRTL and regular WRTI is given.
It is proved that DLL proof search algorithms that use clause learning based
on unit propagation can be polynomially simulated by regular WRTI. More
generally, non-greedy DLL algorithms with learning by unit propagation are
equivalent to regular WRTI. A general form of clause learning, called
DLL-Learn, is defined that is equivalent to regular WRTL.
A variable extension method is used to give simulations of resolution by
regular WRTI, using a simplified form of proof trace extensions. DLL-Learn and
non-greedy DLL algorithms with learning by unit propagation can use variable
extensions to simulate general resolution without doing restarts.
Finally, an exponential lower bound for WRTL where the lemmas are restricted
to short clauses is shown
Short Propositional Refutations for Dense Random 3CNF Formulas
Random 3CNF formulas constitute an important distribution for measuring the
average-case behavior of propositional proof systems. Lower bounds for random
3CNF refutations in many propositional proof systems are known. Most notably
are the exponential-size resolution refutation lower bounds for random 3CNF
formulas with clauses [Chvatal and Szemeredi
(1988), Ben-Sasson and Wigderson (2001)]. On the other hand, the only known
non-trivial upper bound on the size of random 3CNF refutations in a
non-abstract propositional proof system is for resolution with
clauses, shown by Beame et al. (2002). In this paper we
show that already standard propositional proof systems, within the hierarchy of
Frege proofs, admit short refutations for random 3CNF formulas, for
sufficiently large clause-to-variable ratio. Specifically, we demonstrate
polynomial-size propositional refutations whose lines are formulas
(i.e., -Frege proofs) for random 3CNF formulas with variables and clauses.
The idea is based on demonstrating efficient propositional correctness proofs
of the random 3CNF unsatisfiability witnesses given by Feige, Kim and Ofek
(2006). Since the soundness of these witnesses is verified using spectral
techniques, we develop an appropriate way to reason about eigenvectors in
propositional systems. To carry out the full argument we work inside weak
formal systems of arithmetic and use a general translation scheme to
propositional proofs.Comment: 62 pages; improved introduction and abstract, and a changed title.
Fixed some typo
Automating Resolution is NP-Hard
We show that the problem of finding a Resolution refutation that is at most
polynomially longer than a shortest one is NP-hard. In the parlance of proof
complexity, Resolution is not automatizable unless P = NP. Indeed, we show it
is NP-hard to distinguish between formulas that have Resolution refutations of
polynomial length and those that do not have subexponential length refutations.
This also implies that Resolution is not automatizable in subexponential time
or quasi-polynomial time unless NP is included in SUBEXP or QP, respectively
Narrow proofs may be maximally long
We prove that there are 3-CNF formulas over n variables that can be refuted in resolution in width w but require resolution proofs of size n(Omega(w)). This shows that the simple counting argument that any formula refutable in width w must have a proof in size n(O(w)) is essentially tight. Moreover, our lower bound generalizes to polynomial calculus resolution and Sherali-Adams, implying that the corresponding size upper bounds in terms of degree and rank are tight as well. The lower bound does not extend all the way to Lasserre, however, since we show that there the formulas we study have proofs of constant rank and size polynomial in both n and w.Peer ReviewedPostprint (author's final draft
Narrow Proofs May Be Maximally Long
We prove that there are 3-CNF formulas over n variables that can be refuted
in resolution in width w but require resolution proofs of size n^Omega(w). This
shows that the simple counting argument that any formula refutable in width w
must have a proof in size n^O(w) is essentially tight. Moreover, our lower
bound generalizes to polynomial calculus resolution (PCR) and Sherali-Adams,
implying that the corresponding size upper bounds in terms of degree and rank
are tight as well. Our results do not extend all the way to Lasserre, however,
where the formulas we study have proofs of constant rank and size polynomial in
both n and w
On SAT representations of XOR constraints
We study the representation of systems S of linear equations over the
two-element field (aka xor- or parity-constraints) via conjunctive normal forms
F (boolean clause-sets). First we consider the problem of finding an
"arc-consistent" representation ("AC"), meaning that unit-clause propagation
will fix all forced assignments for all possible instantiations of the
xor-variables. Our main negative result is that there is no polysize
AC-representation in general. On the positive side we show that finding such an
AC-representation is fixed-parameter tractable (fpt) in the number of
equations. Then we turn to a stronger criterion of representation, namely
propagation completeness ("PC") --- while AC only covers the variables of S,
now all the variables in F (the variables in S plus auxiliary variables) are
considered for PC. We show that the standard translation actually yields a PC
representation for one equation, but fails so for two equations (in fact
arbitrarily badly). We show that with a more intelligent translation we can
also easily compute a translation to PC for two equations. We conjecture that
computing a representation in PC is fpt in the number of equations.Comment: 39 pages; 2nd v. improved handling of acyclic systems, free-standing
proof of the transformation from AC-representations to monotone circuits,
improved wording and literature review; 3rd v. updated literature,
strengthened treatment of monotonisation, improved discussions; 4th v. update
of literature, discussions and formulations, more details and examples;
conference v. to appear LATA 201
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