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Optimal Complexity Bounds for Positive LTL Games

机译:积极的LTL游戏的最佳复杂性界限

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We prove two tight bounds on complexity of deciding graph games with winning conditions defined by formulas from fragments of LTL. Our first result is that deciding LTL_+ (◇, ∧, ∨) games is in PSPACE. This is a tight bound: the problem is known to be PSPACE-hard even for the much weaker logic LTL_+(◇, ∧). We use a method based on a notion of, as we call it, persistent strategy: we prove that in games with positive winning condition the opponent has a winning strategy if and only if he has a persistent winning strategy. The best upper bound one can prove for our problem with the Buechi automata technique, is EXPSPACE. This means that we identify a natural fragment of LTL for which the algorithm resulting from the Biichi automata tool is one exponent worse than optimal. As our second result we show that the problem is EXPSPACE-hard if the winning condition is from the logic LTL_+(◇, ○, ∧, ∨). This solves an open problem from [AT01], where the authors use the Biichi automata technique to show an EXPSPACE algorithm deciding more general LTL(◇, ○, ∧, ∨) games, but do not prove optimality of this upper bound.
机译:我们证明了决定图博弈的复杂性有两个严格的界限,图博弈的获胜条件由LTL片段的公式定义。我们的第一个结果是决定LTL_ +(◇,∧,∨)游戏在PSPACE中。这是一个严格的界限:即使对于逻辑LTL _ +(◇,∧)弱得多的问题,也知道问题是PSPACE难以解决的。我们使用一种基于持久策略的方法:我们证明在具有正获胜条件的游戏中,当且仅当对手具有持久获胜策略时,对手才具有获胜策略。 Buechi自动机技术可以证明我们的问题的最佳上限是EXPSPACE。这意味着我们确定了LTL的天然片段,根据Biichi自动机工具得出的算法,该片段的性能比最佳性能差一个指数。作为我们的第二个结果,我们证明了如果获胜条件来自逻辑LTL _ +(◇,○,∧,∨),则问题为EXPSPACE-hard。这解决了[AT01]中的一个开放问题,在该问题中,作者使用Biichi自动机技术展示了EXPSPACE算法,该算法决定了更一般的LTL(◇,○,∧,∨)游戏,但没有证明该上限的最优性。

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