Deciding parity games in quasipolynomial time

Calude, Cristian S.; Jain, Sanjay; Khoussainov, Bakhadyr; Li, Wei; Stephan, Frank

doi:10.1145/3055399.3055409

Cited by 120 publications

(186 citation statements)

References 39 publications

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“…Our contribution is to prove that every progress measure on a finite game graph is-in an appropriate sense-equivalent to a succinctly represented progress measure. This paves the way to the design of an algorithm that slightly improves the quasipolynomial time complexity of the algorithm of Calude et al [4], and that significantly improves the space complexity from quasi-polynomial down to nearly linear.…”

Section: Our Contributionmentioning

confidence: 83%

“…After decades of algorithmic improvements for the modal mu-calculus model checking [8], [3], [26] and for solving parity games [13], [15], [25], [5], [21], a recent breakthrough came from Calude et al [4] who gave the first algorithm that works in quasi-polynomial time, where the best upper bounds known previously were subexponential of the form n O( √ n) [15], [21]. Remarkably, Calude et al have also established fixed parameter tractability for the key parameter d-the number of distinct vertex priorities.…”

Section: A Parity Gamesmentioning

confidence: 99%

“…Our work is inspired by the succinct counting technique of Calude et al [4], but it is otherwise rooted in earlier work on 978-1-5090-3018-7/17/$31.00 c 2017 IEEE rankings and progress measures [6], [19], [27], and in particular it is centered on their uses for algorithmically solving games on finite game graphs [13], [24], [25].…”

Section: B Progress Measuresmentioning

confidence: 99%

See 2 more Smart Citations

Succinct progress measures for solving parity games

Jurdziński

Lazić

2017

2017 32nd Annual ACM/IEEE Symposium on Logic in Computer Science (LICS)

167

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Section: Our Contributionmentioning

confidence: 83%

Section: A Parity Gamesmentioning

confidence: 99%

See 1 more Smart Citation

Succinct progress measures for solving parity games

Jurdziński

Lazić

2017

2017 32nd Annual ACM/IEEE Symposium on Logic in Computer Science (LICS)

167

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“…ltlsynt implements two algorithms that solve such parity games: the well-known recursive algorithm by Zielonka [44], and the recent quasi-polynomial time algorithm by Calude et al [10]. Note that the parity automata (and hence the parity games) produced by Spot are transition-based: priorities label transitions, not states.…”

Section: New Entrant: Bowsermentioning

confidence: 99%

“…Implementation, Availability Acacia4Aiger is implemented in Python and C. It uses the AaPAL library 10 for the manipulation of antichains, and the Speculoos tools 11 to generate AIGER circuits. The source code of Acacia4Aiger is available online at: https://github.com/gaperez64/acacia4aiger.…”

Section: Updated Tool: Acacia4aigermentioning

confidence: 99%

The 4th Reactive Synthesis Competition (SYNTCOMP 2017): Benchmarks, Participants & Results

Jacobs

Basset

Bloem

et al. 2017

Electron. Proc. Theor. Comput. Sci.

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We report on the fourth reactive synthesis competition (SYNTCOMP 2017). We introduce two new benchmark classes that have been added to the SYNTCOMP library, and briefly describe the benchmark selection, evaluation scheme and the experimental setup of SYNTCOMP 2017. We present the participants of SYNTCOMP 2017, with a focus on changes with respect to the previous years and on the two completely new tools that have entered the competition. Finally, we present and analyze the results of our experimental evaluation, including a ranking of tools with respect to quantity and quality of solutions.

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Toward a multilevel scalable parallel Zielonka's algorithm for solving parity games

D’Amore

Murano

Sorrentino

et al. 2020

Concurrency and Computation

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Summary In this work, we perform the feasibility analysis of a multi‐grained parallel version of the Zielonka Recursive (ZR) algorithm exploiting the coarse‐ and fine‐ grained concurrency. Coarse‐grained parallelism relies on a suitable splitting of the problem, that is, a graph decomposition based on its Strongly Connected Components (SCC) or a splitting of the formula generating the game, while fine‐grained parallelism is introduced inside the Attractor which is the most intensive computational kernel. This configuration is new and addressed for the first time in this article. Innovation goes from the introduction of properly defined metrics for the strong and weak scaling of the algorithm. These metrics conduct to an analysis of the values of these metrics for the fine grained algorithm, we can infer the expected performance of the multi‐grained parallel algorithm running in a distributed and hybrid computing environment. Results confirm that while a fine‐grained parallelism have a clear performance limitation, the performance gain we can expect to get by employing a multilevel parallelism is significant.

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Deciding parity games in quasipolynomial time

Cited by 120 publications

References 39 publications

Succinct progress measures for solving parity games

Succinct progress measures for solving parity games

The 4th Reactive Synthesis Competition (SYNTCOMP 2017): Benchmarks, Participants & Results

Toward a multilevel scalable parallel Zielonka's algorithm for solving parity games

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