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arXiv 1801.09618cs.GTcs.LO
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奇偶对策的最优值迭代算法

An Optimal Value Iteration Algorithm for Parity Games

Nathanaël Fijalkow

摘要:

2017年,当两种不同的准多项式时间算法被构造出来时,对解决奇偶博弈的多项式时间算法的探索获得了动力。本文进一步分析了Jurdziski和Lazić提出的第二种算法,称之为简洁进度度量算法。它是作为对以前称为小进度度量算法的算法的改进而提出的,使用了更好的数据结构。本文的出发点是观察到的底层数据结构的进度测量算法是(子图)通用树。我们表明,实际上任何通用树产生一个值迭代算法的一个简洁的进展措施,和算法的复杂性是成比例的大小所选择的通用树。然后,我们表明,这两种算法的通用树的两个结构,第一个指数的大小(小进展措施)和第二个quasipolynomial大小(简洁的进展措施)的通用算法的实例。本文的技术结果是表明后一种构造是渐进紧的:通用树至少具有拟多项式大小。这表明Jurdzienski和Lazić的简洁进度度量算法在这个框架中是最优的,而奇偶博弈的多项式时间算法隐藏在其他地方。

英文摘要:

The quest for a polynomial time algorithm for solving parity games gained momentum in 2017 when two different quasipolynomial time algorithms were constructed. In this paper, we further analyse the second algorithm due to Jurdziński and Lazić and called the succinct progress measure algorithm. It was presented as an improvement over a previous algorithm called the small progress measure algorithm, using a better data structure. The starting point of this paper is the observation that the underlying data structure for both progress measure algorithms are (subgraph-)universal trees. We show that in fact any universal tree gives rise to a value iteration algorithm à la succinct progress measure, and the complexity of the algorithm is proportional to the size of the chosen universal tree. We then show that both algorithms are instances of this generic algorithm for two constructions of universal trees, the first of exponential size (for small progress measure) and the second of quasipolynomial size (for succinct progress measure). The technical result of this paper is to show that the latter construction is asymptotically tight: universal trees have at least quasipolynomial size. This suggests that the succinct progress measure algorithm of Jurdziński and Lazić is in this framework optimal, and that the polynomial time algorithm for parity games is hiding someplace else.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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