10,014 research outputs found
Parameterized Linear Temporal Logics Meet Costs: Still not Costlier than LTL
We continue the investigation of parameterized extensions of Linear Temporal
Logic (LTL) that retain the attractive algorithmic properties of LTL: a
polynomial space model checking algorithm and a doubly-exponential time
algorithm for solving games. Alur et al. and Kupferman et al. showed that this
is the case for Parametric LTL (PLTL) and PROMPT-LTL respectively, which have
temporal operators equipped with variables that bound their scope in time.
Later, this was also shown to be true for Parametric LDL (PLDL), which extends
PLTL to be able to express all omega-regular properties.
Here, we generalize PLTL to systems with costs, i.e., we do not bound the
scope of operators in time, but bound the scope in terms of the cost
accumulated during time. Again, we show that model checking and solving games
for specifications in PLTL with costs is not harder than the corresponding
problems for LTL. Finally, we discuss PLDL with costs and extensions to
multiple cost functions.Comment: In Proceedings GandALF 2015, arXiv:1509.0685
Visibly Linear Dynamic Logic
We introduce Visibly Linear Dynamic Logic (VLDL), which extends Linear
Temporal Logic (LTL) by temporal operators that are guarded by visibly pushdown
languages over finite words. In VLDL one can, e.g., express that a function
resets a variable to its original value after its execution, even in the
presence of an unbounded number of intermediate recursive calls. We prove that
VLDL describes exactly the -visibly pushdown languages. Thus it is
strictly more expressive than LTL and able to express recursive properties of
programs with unbounded call stacks.
The main technical contribution of this work is a translation of VLDL into
-visibly pushdown automata of exponential size via one-way alternating
jumping automata. This translation yields exponential-time algorithms for
satisfiability, validity, and model checking. We also show that visibly
pushdown games with VLDL winning conditions are solvable in triply-exponential
time. We prove all these problems to be complete for their respective
complexity classes.Comment: 25 Page
Finite-state Strategies in Delay Games (full version)
What is a finite-state strategy in a delay game? We answer this surprisingly
non-trivial question by presenting a very general framework that allows to
remove delay: finite-state strategies exist for all winning conditions where
the resulting delay-free game admits a finite-state strategy. The framework is
applicable to games whose winning condition is recognized by an automaton with
an acceptance condition that satisfies a certain aggregation property. Our
framework also yields upper bounds on the complexity of determining the winner
of such delay games and upper bounds on the necessary lookahead to win the
game. In particular, we cover all previous results of that kind as special
cases of our uniform approach
How Much Lookahead is Needed to Win Infinite Games?
Delay games are two-player games of infinite duration in which one player may
delay her moves to obtain a lookahead on her opponent's moves. For
-regular winning conditions it is known that such games can be solved
in doubly-exponential time and that doubly-exponential lookahead is sufficient.
We improve upon both results by giving an exponential time algorithm and an
exponential upper bound on the necessary lookahead. This is complemented by
showing EXPTIME-hardness of the solution problem and tight exponential lower
bounds on the lookahead. Both lower bounds already hold for safety conditions.
Furthermore, solving delay games with reachability conditions is shown to be
PSPACE-complete.
This is a corrected version of the paper https://arxiv.org/abs/1412.3701v4
published originally on August 26, 2016
Prompt Delay
Delay games are two-player games of infinite duration in which one player may
delay her moves to obtain a lookahead on her opponent's moves. Recently, such
games with quantitative winning conditions in weak MSO with the unbounding
quantifier were studied, but their properties turned out to be unsatisfactory.
In particular, unbounded lookahead is in general necessary. Here, we study
delay games with winning conditions given by Prompt-LTL, Linear Temporal Logic
equipped with a parameterized eventually operator whose scope is bounded. Our
main result shows that solving Prompt-LTL delay games is complete for
triply-exponential time. Furthermore, we give tight triply-exponential bounds
on the necessary lookahead and on the scope of the parameterized eventually
operator. Thus, we identify Prompt-LTL as the first known class of well-behaved
quantitative winning conditions for delay games. Finally, we show that applying
our techniques to delay games with \omega-regular winning conditions answers
open questions in the cases where the winning conditions are given by
non-deterministic, universal, or alternating automata
Parametric Linear Dynamic Logic
We introduce Parametric Linear Dynamic Logic (PLDL), which extends Linear
Dynamic Logic (LDL) by temporal operators equipped with parameters that bound
their scope. LDL was proposed as an extension of Linear Temporal Logic (LTL)
that is able to express all -regular specifications while still
maintaining many of LTL's desirable properties like an intuitive syntax and a
translation into non-deterministic B\"uchi automata of exponential size. But
LDL lacks capabilities to express timing constraints. By adding parameterized
operators to LDL, we obtain a logic that is able to express all
-regular properties and that subsumes parameterized extensions of LTL
like Parametric LTL and PROMPT-LTL. Our main technical contribution is a
translation of PLDL formulas into non-deterministic B\"uchi word automata of
exponential size via alternating automata. This yields a PSPACE model checking
algorithm and a realizability algorithm with doubly-exponential running time.
Furthermore, we give tight upper and lower bounds on optimal parameter values
for both problems. These results show that PLDL model checking and
realizability are not harder than LTL model checking and realizability.Comment: In Proceedings GandALF 2014, arXiv:1408.556
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