1,988 research outputs found
Revisiting Synthesis for One-Counter Automata
We study the (parameter) synthesis problem for one-counter automata with
parameters. One-counter automata are obtained by extending classical
finite-state automata with a counter whose value can range over non-negative
integers and be tested for zero. The updates and tests applicable to the
counter can further be made parametric by introducing a set of integer-valued
variables called parameters. The synthesis problem for such automata asks
whether there exists a valuation of the parameters such that all infinite runs
of the automaton satisfy some omega-regular property. Lechner showed that (the
complement of) the problem can be encoded in a restricted one-alternation
fragment of Presburger arithmetic with divisibility. In this work (i) we argue
that said fragment, called AERPADPLUS, is unfortunately undecidable.
Nevertheless, by a careful re-encoding of the problem into a decidable
restriction of AERPADPLUS, (ii) we prove that the synthesis problem is
decidable in general and in N2EXP for several fixed omega-regular properties.
Finally, (iii) we give a polynomial-space algorithm for the special case of the
problem where parameters can only be used in tests, and not updates, of the
counter
Looking at Mean-Payoff through Foggy Windows
Mean-payoff games (MPGs) are infinite duration two-player zero-sum games
played on weighted graphs. Under the hypothesis of perfect information, they
admit memoryless optimal strategies for both players and can be solved in
NP-intersect-coNP. MPGs are suitable quantitative models for open reactive
systems. However, in this context the assumption of perfect information is not
always realistic. For the partial-observation case, the problem that asks if
the first player has an observation-based winning strategy that enforces a
given threshold on the mean-payoff, is undecidable. In this paper, we study the
window mean-payoff objectives that were introduced recently as an alternative
to the classical mean-payoff objectives. We show that, in sharp contrast to the
classical mean-payoff objectives, some of the window mean-payoff objectives are
decidable in games with partial-observation
Robustness Verification for Classifier Ensembles
We give a formal verification procedure that decides whether a classifier
ensemble is robust against arbitrary randomized attacks. Such attacks consist
of a set of deterministic attacks and a distribution over this set. The
robustness-checking problem consists of assessing, given a set of classifiers
and a labelled data set, whether there exists a randomized attack that induces
a certain expected loss against all classifiers. We show the NP-hardness of the
problem and provide an upper bound on the number of attacks that is sufficient
to form an optimal randomized attack. These results provide an effective way to
reason about the robustness of a classifier ensemble. We provide SMT and MILP
encodings to compute optimal randomized attacks or prove that there is no
attack inducing a certain expected loss. In the latter case, the classifier
ensemble is provably robust. Our prototype implementation verifies multiple
neural-network ensembles trained for image-classification tasks. The
experimental results using the MILP encoding are promising both in terms of
scalability and the general applicability of our verification procedure
Compositional Algorithms for Succinct Safety Games
We study the synthesis of circuits for succinct safety specifications given
in the AIG format. We show how AIG safety specifications can be decomposed
automatically into sub specifications. Then we propose symbolic compositional
algorithms to solve the synthesis problem compositionally starting for the
sub-specifications. We have evaluated the compositional algorithms on a set of
benchmarks including those proposed for the first synthesis competition
organised in 2014 by the Synthesis Workshop affiliated to the CAV conference.
We show that a large number of benchmarks can be decomposed automatically and
solved more efficiently with the compositional algorithms that we propose in
this paper.Comment: In Proceedings SYNT 2015, arXiv:1602.0078
Ocho décadas de «cuestión kurda» (1923-2003): Un foco de tensión en el Medio y Próximo Oriente.
Frustrado un primer intento panislámico con la desaparición del Imperio Otomano, a partir de los años de entreguerras y, sobre todo, después de la Segunda Guerra Mundial el Oriente Medio y Próximo ha vivido en permanente conflicto. Uno de estos conflictos ha estado alimentado durante las últimas ocho décadas por la pervivencia de la «cuestión Kurda»
AbsSynthe: abstract synthesis from succinct safety specifications
In this paper, we describe a synthesis algorithm for safety specifications
described as circuits. Our algorithm is based on fixpoint computations,
abstraction and refinement, it uses binary decision diagrams as symbolic data
structure. We evaluate our tool on the benchmarks provided by the organizers of
the synthesis competition organized within the SYNT'14 workshop.Comment: In Proceedings SYNT 2014, arXiv:1407.493
Quantitative Games under Failures
We study a generalisation of sabotage games, a model of dynamic network games
introduced by van Benthem. The original definition of the game is inherently
finite and therefore does not allow one to model infinite processes. We propose
an extension of the sabotage games in which the first player (Runner) traverses
an arena with dynamic weights determined by the second player (Saboteur). In
our model of quantitative sabotage games, Saboteur is now given a budget that
he can distribute amongst the edges of the graph, whilst Runner attempts to
minimise the quantity of budget witnessed while completing his task. We show
that, on the one hand, for most of the classical cost functions considered in
the literature, the problem of determining if Runner has a strategy to ensure a
cost below some threshold is EXPTIME-complete. On the other hand, if the budget
of Saboteur is fixed a priori, then the problem is in PTIME for most cost
functions. Finally, we show that restricting the dynamics of the game also
leads to better complexity
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