奇偶校验游戏的不动点迭代算法

Florian Bruse, M. Falk, M. Lange
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引用次数: 13

摘要

已知模态模微积分的模型检验问题可简化为奇偶对策的求解问题,反之亦然。后者由Walukiewicz公式实现,该公式由奇偶博弈中的一个节点满足,如果玩家0从该节点赢得博弈。因此,他们定义了她的获胜区域,并且任何模态模微积分的模型检查算法,适当地专门用于Walukiewicz公式,都会产生解决奇偶博弈的算法。本文研究了采用最直接的mu-微积分模型检验算法——不动点迭代的效果。这也是为数不多的算法之一,如果不是唯一的,最初不是为奇偶校验游戏解决而设计的。虽然实证研究很快表明,这并不能产生在实践中有效的算法,但从理论角度来看,它很有趣,有两个原因:首先,它是指数型的,几乎所有游戏都被设计为非常特定算法的下限,这表明定点迭代与所有这些都有关。其次,不动点迭代不计算位置制胜策略。注意,Walukiewicz公式只定义获胜区域;为了使该算法计算获胜策略,需要做一些额外的工作。我们展示了这些特殊的指数空间策略我们称之为最终位置策略,我们展示了如何从中提取位置策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Fixpoint-Iteration Algorithm for Parity Games
It is known that the model checking problem for the modal mu-calculus reduces to the problem of solving a parity game and vice-versa. The latter is realised by the Walukiewicz formulas which are satisfied by a node in a parity game iff player 0 wins the game from this node. Thus, they define her winning region, and any model checking algorithm for the modal mu-calculus, suitably specialised to the Walukiewicz formulas, yields an algorithm for solving parity games. In this paper we study the effect of employing the most straight-forward mu-calculus model checking algorithm: fixpoint iteration. This is also one of the few algorithms, if not the only one, that were not originally devised for parity game solving already. While an empirical study quickly shows that this does not yield an algorithm that works well in practice, it is interesting from a theoretical point for two reasons: first, it is exponential on virtually all families of games that were designed as lower bounds for very particular algorithms suggesting that fixpoint iteration is connected to all those. Second, fixpoint iteration does not compute positional winning strategies. Note that the Walukiewicz formulas only define winning regions; some additional work is needed in order to make this algorithm compute winning strategies. We show that these are particular exponential-space strategies which we call eventually-positional, and we show how positional ones can be extracted from them.
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