论文标题
策略逻辑与不完美的信息
Strategy Logic with Imperfect Information
论文作者
论文摘要
我们介绍了不完美的信息设置的策略逻辑的扩展,称为SLII,并研究其模型检查问题。由于这种逻辑自然会用不完美的信息捕获多玩家游戏,因此该问题是不可确定的。但是,我们引入了句法类别的“分层实例”类别,在直觉上,随着一个公式的句法树,策略量化与模型的更精细观察有关,我们证明,模型检查SLII限于层次结构实例。为了确定这一结果,我们通过QCTL(一种中介,“低级”逻辑,更适合自动机技术。 QCTL是CTL的延伸,对原子命题进行了二阶定量。我们通过使用观察值的二阶量化符进行参数化二阶量化器,将其扩展到不完美的信息设置。虽然qctlii的模型检查问题通常是不可确定的,但我们确定了分层公式的句法片段,并使用自动机理论方法证明了它是可决定的。我们将结果应用于不完美的信息设置中解决复杂的战略问题。我们首先表明,在具有层次信息的游戏中,可以决定纳什均衡的确定性策略。我们还引入了分布式有理综合,将有理综合的概括性概括为不完美的信息设置。因为它可以在我们的逻辑中很容易表达,所以我们的主要结果为层次信息提供了解决此问题的解决方案。
We introduce an extension of Strategy Logic for the imperfect-information setting, called SLii, and study its model-checking problem. As this logic naturally captures multi-player games with imperfect information, this problem is undecidable; but we introduce a syntactical class of "hierarchical instances" for which, intuitively, as one goes down the syntactic tree of the formula, strategy quantifications are concerned with finer observations of the model, and we prove that model-checking SLii restricted to hierarchical instances is decidable. To establish this result we go through QCTL, an intermediary, "low-level" logic much more adapted to automata techniques. QCTL is an extension of CTL with second-order quantification over atomic propositions. We extend it to the imperfect information setting by parameterising second-order quantifiers with observations. While the model-checking problem of QCTLii is, in general, undecidable, we identify a syntactic fragment of hierarchical formulas and prove, using an automata-theoretic approach, that it is decidable. We apply our result to solve complex strategic problems in the imperfect-information setting. We first show that the existence of Nash equilibria for deterministic strategies is decidable in games with hierarchical information. We also introduce distributed rational synthesis, a generalisation of rational synthesis to the imperfect-information setting. Because it can easily be expressed in our logic, our main result provides solution to this problem in the case of hierarchical information.