2017 32nd Annual ACM/IEEE Symposium on Logic in Computer Science (LICS) 2017
DOI: 10.1109/lics.2017.8005092
|View full text |Cite
|
Sign up to set email alerts
|

Succinct progress measures for solving parity games

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

7
167
0

Year Published

2018
2018
2021
2021

Publication Types

Select...
5
2

Relationship

0
7

Authors

Journals

citations
Cited by 62 publications
(181 citation statements)
references
References 22 publications
7
167
0
Order By: Relevance
“…We argue that in the separation approach, it is appropriate to slightly adjust the choice of languages to be separated, from EvenLoops n and OddLoops n proposed by Bojańczyk and Czerwiński [3] to the more suitable EvenCycles n and OddCycles n (see Section 3.1 for the definitions). We also verify, in Section 4, that all the three distinct techniques of solving parity games in quasi-polynomial time considered in the recent literature (play summaries [5,20,16], progress measures [25], and register games [27]) yield separators for languages EvenCycles n and LimsupOdd, which (as we argue in Section 3.2) makes them suitable for the separation approach.…”
Section: Our Contributionsupporting
confidence: 58%
See 1 more Smart Citation
“…We argue that in the separation approach, it is appropriate to slightly adjust the choice of languages to be separated, from EvenLoops n and OddLoops n proposed by Bojańczyk and Czerwiński [3] to the more suitable EvenCycles n and OddCycles n (see Section 3.1 for the definitions). We also verify, in Section 4, that all the three distinct techniques of solving parity games in quasi-polynomial time considered in the recent literature (play summaries [5,20,16], progress measures [25], and register games [27]) yield separators for languages EvenCycles n and LimsupOdd, which (as we argue in Section 3.2) makes them suitable for the separation approach.…”
Section: Our Contributionsupporting
confidence: 58%
“…The significance of our main technical results is that they provide evidence against the hope that any of the existing technical approaches to developing quasipolynomial algorithms for solving parity games [5,25,16,27] may lead to further improvements to sub-quasipolynomial algorithms. In other words, our quasipolynomial lower bounds for universal trees and separators form a barrier that all existing approaches must overcome in the ongoing quest for a polynomial-time algorithm for solving parity games.…”
Section: Our Contributionmentioning
confidence: 93%
“…We believe that the integration approach we devised is general enough to be applied to other types of games. In particular, the application of quasi dominions in conjunction with progress measure based approaches, such as those of [27] and [21], may lead to practically efficient quasi polynomial algorithms for parity games and their quantitative extensions.…”
Section: Discussionmentioning
confidence: 99%
“…While subexponential solving algorithms have been devised, despite the (deceptive) simplicity of the game and a continuous research effort, no polynomial time algorithm for solving parity games has been found. However, only recently the problem was shown to be solvable in quasi-polynomial time [10,22,17].…”
Section: Introductionmentioning
confidence: 99%
“…Algorithms from the SI category directly compute the winning strategies for both players; e.g., by means of policy iteration or by maintaining some statistics about the plays that can emerge from a vertex. The recent quasi-polynomial algorithms [10,22,17] all fall in this category, but also classical algorithms such as Jurdziński's small progress measures algorithm [21], and, to some extent, the Fixpoint-Iteration (FI) algorithm [8], which is closely related to the small progress measures algorithm, see ibid. The DI category of algorithms proceed by (recursively) decomposing the game graph in dominions: small subgraphs that are won by a single player and from which the opponent cannot escape.…”
Section: Introductionmentioning
confidence: 99%