94 research outputs found
Quasipolynomial Set-Based Symbolic Algorithms for Parity Games
Solving parity games, which are equivalent to modal -calculus model
checking, is a central algorithmic problem in formal methods. Besides the
standard computation model with the explicit representation of games, another
important theoretical model of computation is that of set-based symbolic
algorithms. Set-based symbolic algorithms use basic set operations and one-step
predecessor operations on the implicit description of games, rather than the
explicit representation. The significance of symbolic algorithms is that they
provide scalable algorithms for large finite-state systems, as well as for
infinite-state systems with finite quotient. Consider parity games on graphs
with vertices and parity conditions with priorities. While there is a
rich literature of explicit algorithms for parity games, the main results for
set-based symbolic algorithms are as follows: (a) an algorithm that requires
symbolic operations and symbolic space; and (b) an improved
algorithm that requires symbolic operations and symbolic
space. Our contributions are as follows: (1) We present a black-box set-based
symbolic algorithm based on the explicit progress measure algorithm. Two
important consequences of our algorithm are as follows: (a) a set-based
symbolic algorithm for parity games that requires quasi-polynomially many
symbolic operations and symbolic space; and (b) any future improvement
in progress measure based explicit algorithms imply an efficiency improvement
in our set-based symbolic algorithm for parity games. (2) We present a
set-based symbolic algorithm that requires quasi-polynomially many symbolic
operations and symbolic space. Moreover, for the important
special case of , our algorithm requires only polynomially many
symbolic operations and poly-logarithmic symbolic space.Comment: Published at LPAR-22 in 201
Solving parity games: Explicit vs symbolic
In this paper we provide a broad investigation of the symbolic approach for solving Parity Games. Specifically, we implement in a fresh tool, called, four symbolic algorithms to solve Parity Games and compare their performances to the corresponding explicit versions for different classes of games. By means of benchmarks, we show that for random games, even for constrained random games, explicit algorithms actually perform better than symbolic algorithms. The situation changes, however, for structured games, where symbolic algorithms seem to have the advantage. This suggests that when evaluating algorithms for parity-game solving, it would be useful to have real benchmarks and not only random benchmarks, as the common practice has been
A Universal Attractor Decomposition Algorithm for Parity Games
An attractor decomposition meta-algorithm for solving parity games is given
that generalizes the classic McNaughton-Zielonka algorithm and its recent
quasi-polynomial variants due to Parys (2019), and to Lehtinen, Schewe, and
Wojtczak (2019). The central concepts studied and exploited are attractor
decompositions of dominia in parity games and the ordered trees that describe
the inductive structure of attractor decompositions.
The main technical results include the embeddable decomposition theorem and
the dominion separation theorem that together help establish a precise
structural condition for the correctness of the universal algorithm: it
suffices that the two ordered trees given to the algorithm as inputs embed the
trees of some attractor decompositions of the largest dominia for each of the
two players, respectively.
The universal algorithm yields McNaughton-Zielonka, Parys's, and
Lehtinen-Schewe-Wojtczak algorithms as special cases when suitable universal
trees are given to it as inputs. The main technical results provide a unified
proof of correctness and deep structural insights into those algorithms.
A symbolic implementation of the universal algorithm is also given that
improves the symbolic space complexity of solving parity games in
quasi-polynomial time from ---achieved by Chatterjee,
Dvo\v{r}\'{a}k, Henzinger, and Svozil (2018)---down to , where is
the number of vertices and is the number of distinct priorities in a parity
game. This not only exponentially improves the dependence on , but it also
entirely removes the dependence on
A Comparison of BDD-Based Parity Game Solvers
Parity games are two player games with omega-winning conditions, played on
finite graphs. Such games play an important role in verification,
satisfiability and synthesis. It is therefore important to identify algorithms
that can efficiently deal with large games that arise from such applications.
In this paper, we describe our experiments with BDD-based implementations of
four parity game solving algorithms, viz. Zielonka's recursive algorithm, the
more recent Priority Promotion algorithm, the Fixpoint-Iteration algorithm and
the automata based APT algorithm. We compare their performance on several types
of random games and on a number of cases taken from the Keiren benchmark set.Comment: In Proceedings GandALF 2018, arXiv:1809.0241
Symbolic Parity Game Solvers that Yield Winning Strategies
Parity games play an important role for LTL synthesis as evidenced by recent
breakthroughs on LTL synthesis, which rely in part on parity game solving. Yet
state space explosion remains a major issue if we want to scale to larger
systems or specifications. In order to combat this problem, we need to
investigate symbolic methods such as BDDs, which have been successful in the
past to tackle exponentially large systems. It is therefore essential to have
symbolic parity game solving algorithms, operating using BDDs, that are fast
and that can produce the winning strategies used to synthesize the controller
in LTL synthesis.
Current symbolic parity game solving algorithms do not yield winning
strategies. We now propose two symbolic algorithms that yield winning
strategies, based on two recently proposed fixpoint algorithms. We implement
the algorithms and empirically evaluate them using benchmarks obtained from
SYNTCOMP 2020. Our conclusion is that the algorithms are competitive with or
faster than an earlier symbolic implementation of Zielonka's recursive
algorithm, while also providing the winning strategies.Comment: In Proceedings GandALF 2020, arXiv:2009.0936
The Theory of Universal Graphs for Infinite Duration Games
We introduce the notion of universal graphs as a tool for constructing
algorithms solving games of infinite duration such as parity games and mean
payoff games. In the first part we develop the theory of universal graphs, with
two goals: showing an equivalence and normalisation result between different
recently introduced related models, and constructing generic value iteration
algorithms for any positionally determined objective. In the second part we
give four applications: to parity games, to mean payoff games, and to
combinations of them (in the form of disjunctions of objectives). For each of
these four cases we construct algorithms achieving or improving over the best
known time and space complexity.Comment: 43 pages, 10 figure
Automating Resolution is NP-Hard
We show that the problem of finding a Resolution refutation that is at most
polynomially longer than a shortest one is NP-hard. In the parlance of proof
complexity, Resolution is not automatizable unless P = NP. Indeed, we show it
is NP-hard to distinguish between formulas that have Resolution refutations of
polynomial length and those that do not have subexponential length refutations.
This also implies that Resolution is not automatizable in subexponential time
or quasi-polynomial time unless NP is included in SUBEXP or QP, respectively
A Recursive Approach to Solving Parity Games in Quasipolynomial Time
Zielonka's classic recursive algorithm for solving parity games is perhaps the simplest among the many existing parity game algorithms. However, its complexity is exponential, while currently the state-of-the-art algorithms have quasipolynomial complexity. Here, we present a modification of Zielonka's classic algorithm that brings its complexity down to , for parity games of size with priorities, in line with previous quasipolynomial-time solutions.</jats:p
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