254 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
Circuit complexity, proof complexity, and polynomial identity testing
We introduce a new algebraic proof system, which has tight connections to
(algebraic) circuit complexity. In particular, we show that any
super-polynomial lower bound on any Boolean tautology in our proof system
implies that the permanent does not have polynomial-size algebraic circuits
(VNP is not equal to VP). As a corollary to the proof, we also show that
super-polynomial lower bounds on the number of lines in Polynomial Calculus
proofs (as opposed to the usual measure of number of monomials) imply the
Permanent versus Determinant Conjecture. Note that, prior to our work, there
was no proof system for which lower bounds on an arbitrary tautology implied
any computational lower bound.
Our proof system helps clarify the relationships between previous algebraic
proof systems, and begins to shed light on why proof complexity lower bounds
for various proof systems have been so much harder than lower bounds on the
corresponding circuit classes. In doing so, we highlight the importance of
polynomial identity testing (PIT) for understanding proof complexity.
More specifically, we introduce certain propositional axioms satisfied by any
Boolean circuit computing PIT. We use these PIT axioms to shed light on
AC^0[p]-Frege lower bounds, which have been open for nearly 30 years, with no
satisfactory explanation as to their apparent difficulty. We show that either:
a) Proving super-polynomial lower bounds on AC^0[p]-Frege implies VNP does not
have polynomial-size circuits of depth d - a notoriously open question for d at
least 4 - thus explaining the difficulty of lower bounds on AC^0[p]-Frege, or
b) AC^0[p]-Frege cannot efficiently prove the depth d PIT axioms, and hence we
have a lower bound on AC^0[p]-Frege.
Using the algebraic structure of our proof system, we propose a novel way to
extend techniques from algebraic circuit complexity to prove lower bounds in
proof complexity
Efficiently Simulating Higher-Order Arithmetic by a First-Order Theory Modulo
In deduction modulo, a theory is not represented by a set of axioms but by a
congruence on propositions modulo which the inference rules of standard
deductive systems---such as for instance natural deduction---are applied.
Therefore, the reasoning that is intrinsic of the theory does not appear in the
length of proofs. In general, the congruence is defined through a rewrite
system over terms and propositions. We define a rigorous framework to study
proof lengths in deduction modulo, where the congruence must be computed in
polynomial time. We show that even very simple rewrite systems lead to
arbitrary proof-length speed-ups in deduction modulo, compared to using axioms.
As higher-order logic can be encoded as a first-order theory in deduction
modulo, we also study how to reinterpret, thanks to deduction modulo, the
speed-ups between higher-order and first-order arithmetics that were stated by
G\"odel. We define a first-order rewrite system with a congruence decidable in
polynomial time such that proofs of higher-order arithmetic can be linearly
translated into first-order arithmetic modulo that system. We also present the
whole higher-order arithmetic as a first-order system without resorting to any
axiom, where proofs have the same length as in the axiomatic presentation
On the proof complexity of logics of bounded branching
We investigate the proof complexity of extended Frege (EF) systems for basic
transitive modal logics (K4, S4, GL, ...) augmented with the bounded branching
axioms . First, we study feasibility of the disjunction property
and more general extension rules in EF systems for these logics: we show that
the corresponding decision problems reduce to total coNP search problems (or
equivalently, disjoint NP pairs, in the binary case); more precisely, the
decision problem for extension rules is equivalent to a certain special case of
interpolation for the classical EF system. Next, we use this characterization
to prove superpolynomial (or even exponential, with stronger hypotheses)
separations between EF and substitution Frege (SF) systems for all transitive
logics contained in or under some
assumptions weaker than . We also prove analogous
results for superintuitionistic logics: we characterize the decision complexity
of multi-conclusion Visser's rules in EF systems for Gabbay--de Jongh logics
, and we show conditional separations between EF and SF for all
intermediate logics contained in .Comment: 58 page
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