447 research outputs found
Observation of implicit complexity by non confluence
We propose to consider non confluence with respect to implicit complexity. We
come back to some well known classes of first-order functional program, for
which we have a characterization of their intentional properties, namely the
class of cons-free programs, the class of programs with an interpretation, and
the class of programs with a quasi-interpretation together with a termination
proof by the product path ordering. They all correspond to PTIME. We prove that
adding non confluence to the rules leads to respectively PTIME, NPTIME and
PSPACE. Our thesis is that the separation of the classes is actually a witness
of the intentional properties of the initial classes of programs
The Complexity of Computing the Size of an Interval
Given a p-order A over a universe of strings (i.e., a transitive, reflexive,
antisymmetric relation such that if (x, y) is an element of A then |x| is
polynomially bounded by |y|), an interval size function of A returns, for each
string x in the universe, the number of strings in the interval between strings
b(x) and t(x) (with respect to A), where b(x) and t(x) are functions that are
polynomial-time computable in the length of x.
By choosing sets of interval size functions based on feasibility requirements
for their underlying p-orders, we obtain new characterizations of complexity
classes. We prove that the set of all interval size functions whose underlying
p-orders are polynomial-time decidable is exactly #P. We show that the interval
size functions for orders with polynomial-time adjacency checks are closely
related to the class FPSPACE(poly). Indeed, FPSPACE(poly) is exactly the class
of all nonnegative functions that are an interval size function minus a
polynomial-time computable function.
We study two important functions in relation to interval size functions. The
function #DIV maps each natural number n to the number of nontrivial divisors
of n. We show that #DIV is an interval size function of a polynomial-time
decidable partial p-order with polynomial-time adjacency checks. The function
#MONSAT maps each monotone boolean formula F to the number of satisfying
assignments of F. We show that #MONSAT is an interval size function of a
polynomial-time decidable total p-order with polynomial-time adjacency checks.
Finally, we explore the related notion of cluster computation.Comment: This revision fixes a problem in the proof of Theorem 9.
A PCP Characterization of AM
We introduce a 2-round stochastic constraint-satisfaction problem, and show
that its approximation version is complete for (the promise version of) the
complexity class AM. This gives a `PCP characterization' of AM analogous to the
PCP Theorem for NP. Similar characterizations have been given for higher levels
of the Polynomial Hierarchy, and for PSPACE; however, we suggest that the
result for AM might be of particular significance for attempts to derandomize
this class.
To test this notion, we pose some `Randomized Optimization Hypotheses'
related to our stochastic CSPs that (in light of our result) would imply
collapse results for AM. Unfortunately, the hypotheses appear over-strong, and
we present evidence against them. In the process we show that, if some language
in NP is hard-on-average against circuits of size 2^{Omega(n)}, then there
exist hard-on-average optimization problems of a particularly elegant form.
All our proofs use a powerful form of PCPs known as Probabilistically
Checkable Proofs of Proximity, and demonstrate their versatility. We also use
known results on randomness-efficient soundness- and hardness-amplification. In
particular, we make essential use of the Impagliazzo-Wigderson generator; our
analysis relies on a recent Chernoff-type theorem for expander walks.Comment: 18 page
Rational Proofs with Multiple Provers
Interactive proofs (IP) model a world where a verifier delegates computation
to an untrustworthy prover, verifying the prover's claims before accepting
them. IP protocols have applications in areas such as verifiable computation
outsourcing, computation delegation, cloud computing. In these applications,
the verifier may pay the prover based on the quality of his work. Rational
interactive proofs (RIP), introduced by Azar and Micali (2012), are an
interactive-proof system with payments, in which the prover is rational rather
than untrustworthy---he may lie, but only to increase his payment. Rational
proofs leverage the provers' rationality to obtain simple and efficient
protocols. Azar and Micali show that RIP=IP(=PSAPCE). They leave the question
of whether multiple provers are more powerful than a single prover for rational
and classical proofs as an open problem.
In this paper, we introduce multi-prover rational interactive proofs (MRIP).
Here, a verifier cross-checks the provers' answers with each other and pays
them according to the messages exchanged. The provers are cooperative and
maximize their total expected payment if and only if the verifier learns the
correct answer to the problem. We further refine the model of MRIP to
incorporate utility gap, which is the loss in payment suffered by provers who
mislead the verifier to the wrong answer.
We define the class of MRIP protocols with constant, noticeable and
negligible utility gaps. We give tight characterization for all three MRIP
classes. We show that under standard complexity-theoretic assumptions, MRIP is
more powerful than both RIP and MIP ; and this is true even the utility gap is
required to be constant. Furthermore the full power of each MRIP class can be
achieved using only two provers and three rounds. (A preliminary version of
this paper appeared at ITCS 2016. This is the full version that contains new
results.)Comment: Proceedings of the 2016 ACM Conference on Innovations in Theoretical
Computer Science. ACM, 201
Formalizing Termination Proofs under Polynomial Quasi-interpretations
Usual termination proofs for a functional program require to check all the
possible reduction paths. Due to an exponential gap between the height and size
of such the reduction tree, no naive formalization of termination proofs yields
a connection to the polynomial complexity of the given program. We solve this
problem employing the notion of minimal function graph, a set of pairs of a
term and its normal form, which is defined as the least fixed point of a
monotone operator. We show that termination proofs for programs reducing under
lexicographic path orders (LPOs for short) and polynomially quasi-interpretable
can be optimally performed in a weak fragment of Peano arithmetic. This yields
an alternative proof of the fact that every function computed by an
LPO-terminating, polynomially quasi-interpretable program is computable in
polynomial space. The formalization is indeed optimal since every
polynomial-space computable function can be computed by such a program. The
crucial observation is that inductive definitions of minimal function graphs
under LPO-terminating programs can be approximated with transfinite induction
along LPOs.Comment: In Proceedings FICS 2015, arXiv:1509.0282
Characterizing small depth and small space classes by operators of higher types
Motivated by the question of how to define an analog of interactive proofs in the setting of logarithmic time- and space-bounded computation, we study complexity classes defined in terms of operators quantifying over oracles. We obtain new characterizations of NC1, L, NL, NP, and NSC (the nondeterministic version of SC). In some cases, we prove that our simulations are optimal (for instance, in bounding the number of queries to the oracle)
Finite state verifiers with constant randomness
We give a new characterization of as the class of languages
whose members have certificates that can be verified with small error in
polynomial time by finite state machines that use a constant number of random
bits, as opposed to its conventional description in terms of deterministic
logarithmic-space verifiers. It turns out that allowing two-way interaction
with the prover does not change the class of verifiable languages, and that no
polynomially bounded amount of randomness is useful for constant-memory
computers when used as language recognizers, or public-coin verifiers. A
corollary of our main result is that the class of outcome problems
corresponding to O(log n)-space bounded games of incomplete information where
the universal player is allowed a constant number of moves equals NL.Comment: 17 pages. An improved versio
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