204 research outputs found
Improving the complexity of Parys' recursive algorithm
Parys has recently proposed a quasi-polynomial version of Zielonka's recursive algorithm for solving parity games. In this brief note we suggest a variation of his algorithm that improves the complexity to meet the state-of-the-art complexity of broadly , while providing polynomial bounds when the number of colours is logarithmic
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 Technique to Speed up Symmetric Attractor-Based Algorithms for Parity Games
The classic McNaughton-Zielonka algorithm for solving parity games has excellent performance in practice, but its worst-case asymptotic complexity is worse than that of the state-of-the-art algorithms. This work pinpoints the mechanism that is responsible for this relative underperformance and proposes a new technique that eliminates it. The culprit is the wasteful manner in which the results obtained from recursive calls are indiscriminately discarded by the algorithm whenever subgames on which the algorithm is run change. Our new technique is based on firstly enhancing the algorithm to compute attractor decompositions of subgames instead of just winning strategies on them, and then on making it carefully use attractor decompositions computed in prior recursive calls to reduce the size of subgames on which further recursive calls are made. We illustrate the new technique on the classic example of the recursive McNaughton-Zielonka algorithm, but it can be applied to other symmetric attractor-based algorithms that were inspired by it, such as the quasi-polynomial versions of the McNaughton-Zielonka algorithm based on universal trees
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
Priority Promotion with Parysian Flair
We develop an algorithm that combines the advantages of priority promotion - one of the leading approaches to solving large parity games in practice - with the quasi-polynomial time guarantees offered by Parys' algorithm. Hybridising these algorithms sounds both natural and difficult, as they both generalise the classic recursive algorithm in different ways that appear to be irreconcilable: while the promotion transcends the call structure, the guarantees change on each level. We show that an interface that respects both is not only effective, but also efficient
A technique to speed up symmetric attractor-based algorithms for parity games
The classic McNaughton-Zielonka algorithm for solving parity games has excellent performance in practice, but its worst-case asymptotic complexity is worse than that of the state-of-the-art algorithms. This work pinpoints the mechanism that is responsible for this relative underperformance and proposes a new technique that eliminates it. The culprit is the wasteful manner in which the results obtained from recursive calls are indiscriminately discarded by the algorithm whenever subgames on which the algorithm is run change. Our new technique is based on firstly enhancing the algorithm to compute attractor decompositions of subgames instead of just winning strategies on them, and then on making it carefully use attractor decompositions computed in prior recursive calls to reduce the size of subgames on which further recursive calls are made. We illustrate the new technique on the classic example of the recursive McNaughton-Zielonka algorithm, but it can be applied to other symmetric attractor-based algorithms that were inspired by it, such as the quasi-polynomial versions of the McNaughton-Zielonka algorithm based on universal trees
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