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Augmenting ATL with strategy contexts

机译:通过策略环境增强ATL

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We study the extension of the alternating-time temporal logic (ATL) with strategy contexts: contrary to the original semantics, in this semantics the strategy quantifiers do not reset the previously selected strategies. We show that our extension ATL_(sc) is very expressive, but that its decision problems are quite hard: model checking is k-EXPTIME-complete when the formula has k nested strategy quantifiers; satisfiability is undecidable, but we prove that it is decidable when restricting to turn-based games. Our algorithms are obtained through a very convenient translation to QCTL (the computation-tree logic CTL extended with atomic quantification), which we show also applies to Strategy Logic, as well as when strategy quantification ranges over memoryless strategies.
机译:我们研究了具有策略上下文的时态时间逻辑(ATL)的扩展:与原始语义相反,在这种语义中,策略量词不会重置先前选择的策略。我们证明了扩展ATL_(sc)的表达能力很强,但是它的决策问题却很困难:当公式具有k个嵌套策略量词时,模型检查是k-EXPTIME-complete;可满足性是无法决定的,但是我们证明了在限制回合制游戏时它是可决定的。我们的算法是通过非常方便地转换为QCTL(使用原子量化扩展的计算树逻辑CTL)而获得的,我们证明了该算法也适用于Strategy Logic,以及策略量化的范围超过无内存策略。

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