626 research outputs found
Exact and Approximate Determinization of Discounted-Sum Automata
A discounted-sum automaton (NDA) is a nondeterministic finite automaton with
edge weights, valuing a run by the discounted sum of visited edge weights. More
precisely, the weight in the i-th position of the run is divided by
, where the discount factor is a fixed rational number
greater than 1. The value of a word is the minimal value of the automaton runs
on it. Discounted summation is a common and useful measuring scheme, especially
for infinite sequences, reflecting the assumption that earlier weights are more
important than later weights. Unfortunately, determinization of NDAs, which is
often essential in formal verification, is, in general, not possible. We
provide positive news, showing that every NDA with an integral discount factor
is determinizable. We complete the picture by proving that the integers
characterize exactly the discount factors that guarantee determinizability: for
every nonintegral rational discount factor , there is a
nondeterminizable -NDA. We also prove that the class of NDAs with
integral discount factors enjoys closure under the algebraic operations min,
max, addition, and subtraction, which is not the case for general NDAs nor for
deterministic NDAs. For general NDAs, we look into approximate determinization,
which is always possible as the influence of a word's suffix decays. We show
that the naive approach, of unfolding the automaton computations up to a
sufficient level, is doubly exponential in the discount factor. We provide an
alternative construction for approximate determinization, which is singly
exponential in the discount factor, in the precision, and in the number of
states. We also prove matching lower bounds, showing that the exponential
dependency on each of these three parameters cannot be avoided. All our results
hold equally for automata over finite words and for automata over infinite
words
Determinacy in Discrete-Bidding Infinite-Duration Games
In two-player games on graphs, the players move a token through a graph to
produce an infinite path, which determines the winner of the game. Such games
are central in formal methods since they model the interaction between a
non-terminating system and its environment. In bidding games the players bid
for the right to move the token: in each round, the players simultaneously
submit bids, and the higher bidder moves the token and pays the other player.
Bidding games are known to have a clean and elegant mathematical structure that
relies on the ability of the players to submit arbitrarily small bids. Many
applications, however, require a fixed granularity for the bids, which can
represent, for example, the monetary value expressed in cents. We study, for
the first time, the combination of discrete-bidding and infinite-duration
games. Our most important result proves that these games form a large
determined subclass of concurrent games, where determinacy is the strong
property that there always exists exactly one player who can guarantee winning
the game. In particular, we show that, in contrast to non-discrete bidding
games, the mechanism with which tied bids are resolved plays an important role
in discrete-bidding games. We study several natural tie-breaking mechanisms and
show that, while some do not admit determinacy, most natural mechanisms imply
determinacy for every pair of initial budgets
Quantitative Automata under Probabilistic Semantics
Automata with monitor counters, where the transitions do not depend on
counter values, and nested weighted automata are two expressive
automata-theoretic frameworks for quantitative properties. For a well-studied
and wide class of quantitative functions, we establish that automata with
monitor counters and nested weighted automata are equivalent. We study for the
first time such quantitative automata under probabilistic semantics. We show
that several problems that are undecidable for the classical questions of
emptiness and universality become decidable under the probabilistic semantics.
We present a complete picture of decidability for such automata, and even an
almost-complete picture of computational complexity, for the probabilistic
questions we consider
Infinite-Duration Bidding Games
Two-player games on graphs are widely studied in formal methods as they model
the interaction between a system and its environment. The game is played by
moving a token throughout a graph to produce an infinite path. There are
several common modes to determine how the players move the token through the
graph; e.g., in turn-based games the players alternate turns in moving the
token. We study the {\em bidding} mode of moving the token, which, to the best
of our knowledge, has never been studied in infinite-duration games. The
following bidding rule was previously defined and called Richman bidding. Both
players have separate {\em budgets}, which sum up to . In each turn, a
bidding takes place: Both players submit bids simultaneously, where a bid is
legal if it does not exceed the available budget, and the higher bidder pays
his bid to the other player and moves the token. The central question studied
in bidding games is a necessary and sufficient initial budget for winning the
game: a {\em threshold} budget in a vertex is a value such that
if Player 's budget exceeds , he can win the game, and if Player 's
budget exceeds , he can win the game. Threshold budgets were previously
shown to exist in every vertex of a reachability game, which have an
interesting connection with {\em random-turn} games -- a sub-class of simple
stochastic games in which the player who moves is chosen randomly. We show the
existence of threshold budgets for a qualitative class of infinite-duration
games, namely parity games, and a quantitative class, namely mean-payoff games.
The key component of the proof is a quantitative solution to strongly-connected
mean-payoff bidding games in which we extend the connection with random-turn
games to these games, and construct explicit optimal strategies for both
players.Comment: A short version appeared in CONCUR 2017. The paper is accepted to
JAC
The Decidability Frontier for Probabilistic Automata on Infinite Words
We consider probabilistic automata on infinite words with acceptance defined
by safety, reachability, B\"uchi, coB\"uchi, and limit-average conditions. We
consider quantitative and qualitative decision problems. We present extensions
and adaptations of proofs for probabilistic finite automata and present a
complete characterization of the decidability and undecidability frontier of
the quantitative and qualitative decision problems for probabilistic automata
on infinite words
Lipschitz Robustness of Finite-state Transducers
We investigate the problem of checking if a finite-state transducer is robust
to uncertainty in its input. Our notion of robustness is based on the analytic
notion of Lipschitz continuity --- a transducer is K-(Lipschitz) robust if the
perturbation in its output is at most K times the perturbation in its input. We
quantify input and output perturbation using similarity functions. We show that
K-robustness is undecidable even for deterministic transducers. We identify a
class of functional transducers, which admits a polynomial time
automata-theoretic decision procedure for K-robustness. This class includes
Mealy machines and functional letter-to-letter transducers. We also study
K-robustness of nondeterministic transducers. Since a nondeterministic
transducer generates a set of output words for each input word, we quantify
output perturbation using set-similarity functions. We show that K-robustness
of nondeterministic transducers is undecidable, even for letter-to-letter
transducers. We identify a class of set-similarity functions which admit
decidable K-robustness of letter-to-letter transducers.Comment: In FSTTCS 201
Quantitative reactive modeling and verification
Formal verification aims to improve the quality of software by detecting errors before they do harm. At the basis of formal verification is the logical notion of correctness, which purports to capture whether or not a program behaves as desired. We suggest that the boolean partition of software into correct and incorrect programs falls short of the practical need to assess the behavior of software in a more nuanced fashion against multiple criteria. We therefore propose to introduce quantitative fitness measures for programs, specifically for measuring the function, performance, and robustness of reactive programs such as concurrent processes. This article describes the goals of the ERC Advanced Investigator Project QUAREM. The project aims to build and evaluate a theory of quantitative fitness measures for reactive models. Such a theory must strive to obtain quantitative generalizations of the paradigms that have been success stories in qualitative reactive modeling, such as compositionality, property-preserving abstraction and abstraction refinement, model checking, and synthesis. The theory will be evaluated not only in the context of software and hardware engineering, but also in the context of systems biology. In particular, we will use the quantitative reactive models and fitness measures developed in this project for testing hypotheses about the mechanisms behind data from biological experiments
Termination Criteria for Solving Concurrent Safety and Reachability Games
We consider concurrent games played on graphs. At every round of a game, each
player simultaneously and independently selects a move; the moves jointly
determine the transition to a successor state. Two basic objectives are the
safety objective to stay forever in a given set of states, and its dual, the
reachability objective to reach a given set of states. We present in this paper
a strategy improvement algorithm for computing the value of a concurrent safety
game, that is, the maximal probability with which player~1 can enforce the
safety objective. The algorithm yields a sequence of player-1 strategies which
ensure probabilities of winning that converge monotonically to the value of the
safety game.
Our result is significant because the strategy improvement algorithm
provides, for the first time, a way to approximate the value of a concurrent
safety game from below. Since a value iteration algorithm, or a strategy
improvement algorithm for reachability games, can be used to approximate the
same value from above, the combination of both algorithms yields a method for
computing a converging sequence of upper and lower bounds for the values of
concurrent reachability and safety games. Previous methods could approximate
the values of these games only from one direction, and as no rates of
convergence are known, they did not provide a practical way to solve these
games
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