864 research outputs found
Analyzing probabilistic pushdown automata
The paper gives a summary of the existing results about algorithmic analysis of probabilistic pushdown automata and their subclasses.V článku je podán přehled známých výsledků o pravděpodobnostních zásobníkových automatech a některých jejich podtřídách
Decisive Markov Chains
We consider qualitative and quantitative verification problems for
infinite-state Markov chains. We call a Markov chain decisive w.r.t. a given
set of target states F if it almost certainly eventually reaches either F or a
state from which F can no longer be reached. While all finite Markov chains are
trivially decisive (for every set F), this also holds for many classes of
infinite Markov chains. Infinite Markov chains which contain a finite attractor
are decisive w.r.t. every set F. In particular, this holds for probabilistic
lossy channel systems (PLCS). Furthermore, all globally coarse Markov chains
are decisive. This class includes probabilistic vector addition systems (PVASS)
and probabilistic noisy Turing machines (PNTM). We consider both safety and
liveness problems for decisive Markov chains, i.e., the probabilities that a
given set of states F is eventually reached or reached infinitely often,
respectively. 1. We express the qualitative problems in abstract terms for
decisive Markov chains, and show an almost complete picture of its decidability
for PLCS, PVASS and PNTM. 2. We also show that the path enumeration algorithm
of Iyer and Narasimha terminates for decisive Markov chains and can thus be
used to solve the approximate quantitative safety problem. A modified variant
of this algorithm solves the approximate quantitative liveness problem. 3.
Finally, we show that the exact probability of (repeatedly) reaching F cannot
be effectively expressed (in a uniform way) in Tarski-algebra for either PLCS,
PVASS or (P)NTM.Comment: 32 pages, 0 figure
Computation with narrow CTCs
We examine some variants of computation with closed timelike curves (CTCs),
where various restrictions are imposed on the memory of the computer, and the
information carrying capacity and range of the CTC. We give full
characterizations of the classes of languages recognized by polynomial time
probabilistic and quantum computers that can send a single classical bit to
their own past. Such narrow CTCs are demonstrated to add the power of limited
nondeterminism to deterministic computers, and lead to exponential speedup in
constant-space probabilistic and quantum computation. We show that, given a
time machine with constant negative delay, one can implement CTC-based
computations without the need to know about the runtime beforehand.Comment: 16 pages. A few typo was correcte
Approximating the Termination Value of One-Counter MDPs and Stochastic Games
One-counter MDPs (OC-MDPs) and one-counter simple stochastic games (OC-SSGs)
are 1-player, and 2-player turn-based zero-sum, stochastic games played on the
transition graph of classic one-counter automata (equivalently, pushdown
automata with a 1-letter stack alphabet). A key objective for the analysis and
verification of these games is the termination objective, where the players aim
to maximize (minimize, respectively) the probability of hitting counter value
0, starting at a given control state and given counter value. Recently, we
studied qualitative decision problems ("is the optimal termination value = 1?")
for OC-MDPs (and OC-SSGs) and showed them to be decidable in P-time (in NP and
coNP, respectively). However, quantitative decision and approximation problems
("is the optimal termination value ? p", or "approximate the termination value
within epsilon") are far more challenging. This is so in part because optimal
strategies may not exist, and because even when they do exist they can have a
highly non-trivial structure. It thus remained open even whether any of these
quantitative termination problems are computable. In this paper we show that
all quantitative approximation problems for the termination value for OC-MDPs
and OC-SSGs are computable. Specifically, given a OC-SSG, and given epsilon >
0, we can compute a value v that approximates the value of the OC-SSG
termination game within additive error epsilon, and furthermore we can compute
epsilon-optimal strategies for both players in the game. A key ingredient in
our proofs is a subtle martingale, derived from solving certain LPs that we can
associate with a maximizing OC-MDP. An application of Azuma's inequality on
these martingales yields a computable bound for the "wealth" at which a "rich
person's strategy" becomes epsilon-optimal for OC-MDPs.Comment: 35 pages, 1 figure, full version of a paper presented at ICALP 2011,
invited for submission to Information and Computatio
07441 Abstracts Collection -- Algorithmic-Logical Theory of Infinite Structures
From 28.10. to 02.11.2007, the Dagstuhl Seminar 07441 ``Algorithmic-Logical Theory of Infinite Structures\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl.
During the seminar, several participants presented their current
research, and ongoing work and open problems were discussed. Abstracts of
the presentations given during the seminar as well as abstracts of
seminar results and ideas are put together in this paper. The first section
describes the seminar topics and goals in general.
Links to extended abstracts or full papers are provided, if available
One-Counter Stochastic Games
We study the computational complexity of basic decision problems for
one-counter simple stochastic games (OC-SSGs), under various objectives.
OC-SSGs are 2-player turn-based stochastic games played on the transition graph
of classic one-counter automata. We study primarily the termination objective,
where the goal of one player is to maximize the probability of reaching counter
value 0, while the other player wishes to avoid this. Partly motivated by the
goal of understanding termination objectives, we also study certain "limit" and
"long run average" reward objectives that are closely related to some
well-studied objectives for stochastic games with rewards. Examples of problems
we address include: does player 1 have a strategy to ensure that the counter
eventually hits 0, i.e., terminates, almost surely, regardless of what player 2
does? Or that the liminf (or limsup) counter value equals infinity with a
desired probability? Or that the long run average reward is >0 with desired
probability? We show that the qualitative termination problem for OC-SSGs is in
NP intersection coNP, and is in P-time for 1-player OC-SSGs, or equivalently
for one-counter Markov Decision Processes (OC-MDPs). Moreover, we show that
quantitative limit problems for OC-SSGs are in NP intersection coNP, and are in
P-time for 1-player OC-MDPs. Both qualitative limit problems and qualitative
termination problems for OC-SSGs are already at least as hard as Condon's
quantitative decision problem for finite-state SSGs.Comment: 20 pages, 1 figure. This is a full version of a paper accepted for
publication in proceedings of FSTTCS 201
Certificates for Probabilistic Pushdown Automata via Optimistic Value Iteration
Probabilistic pushdown automata (pPDA) are a standard model for discrete
probabilistic programs with procedures and recursion. In pPDA, many
quantitative properties are characterized as least fixpoints of polynomial
equation systems. In this paper, we study the problem of certifying that these
quantities lie within certain bounds. To this end, we first characterize the
polynomial systems that admit easy-to-check certificates for validating bounds
on their least fixpoint. Second, we present a sound and complete Optimistic
Value Iteration algorithm for computing such certificates. Third, we show how
certificates for polynomial systems can be transferred to certificates for
various quantitative pPDA properties. Experiments demonstrate that our
algorithm computes succinct certificates for several intricate example programs
as well as stochastic context-free grammars with production rules.Comment: Full version of a paper to appear at TACAS 2023, 30 page
Potential of quantum finite automata with exact acceptance
The potential of the exact quantum information processing is an interesting,
important and intriguing issue. For examples, it has been believed that quantum
tools can provide significant, that is larger than polynomial, advantages in
the case of exact quantum computation only, or mainly, for problems with very
special structures. We will show that this is not the case.
In this paper the potential of quantum finite automata producing outcomes not
only with a (high) probability, but with certainty (so called exactly) is
explored in the context of their uses for solving promise problems and with
respect to the size of automata. It is shown that for solving particular
classes of promise problems, even those without some
very special structure, that succinctness of the exact quantum finite automata
under consideration, with respect to the number of (basis) states, can be very
small (and constant) though it grows proportional to in the case
deterministic finite automata (DFAs) of the same power are used. This is here
demonstrated also for the case that the component languages of the promise
problems solvable by DFAs are non-regular. The method used can be applied in
finding more exact quantum finite automata or quantum algorithms for other
promise problems.Comment: We have improved the presentation of the paper. Accepted to
International Journal of Foundation of Computer Scienc
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