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Checking dynamic consistency of conditional hyper temporal networks via mean payoff games Hardness and (pseudo) singly-exponential time algorithm

机译:通过平均收益博弈硬度和(伪)单指数时间算法检查条件超时态网络的动态一致性

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Conditional Simple Temporal Network (CSTN ) is a constraint-based graph formalism for conditional temporal planning, which may be viewed as an extension of Simple Temporal Networks. Recently, STN s have been generalized into Hyper Temporal Networks (HyTN s), by considering weighted directed hypergraphs where each hyperarc models a disjunctive temporal constraint. We introduce theConditional Hyper Temporal Network (CHyTN)model, a natural extension and generalization of both CSTN s and HyTN s, obtained by blending them together. We show that deciding whether a given CSTN is dynamically-consistent iscoNP-hard, and that deciding whether a given CHyTN is dynamically-consistent isPSPACE-hard. Next, we offer the first deterministic (pseudo) singly-exponential time algorithm for checking DC in CHyTNs and CSTN s. To analyze the computational complexity of the proposed algorithm, we introduce a refined notion of DC, namedϵ-DC, presenting a sharp lower bounding analysis on the critical value of the reaction time where a conditional temporal network transits from being, to not being, dynamically-consistent.
机译:条件简单时态网络(CSTN)是用于条件时态规划的基于约束的图形式主义,可以看作是简单时态网络的扩展。最近,通过考虑加权有向超图(其中每个超弧为分离的时间约束建模),STN已被推广到超时态网络(HyTN)。我们引入了有条件的超时态网络(CHyTN)模型,它是CSTN和HyTN的自然扩展和概括,是通过将它们混合在一起而获得的。我们展示了确定给定CSTN是否动态一致iscoNP-hard,确定给定CHyTN是否动态一致isPSPACE-hard。接下来,我们提供第一种确定性(伪)单指数时间算法,用于检查CHyTN和CSTN中的DC。为了分析所提出算法的计算复杂性,我们引入了一种精确的DC概念,即ϵ-DC,它对反应时间的临界值进行了尖锐的下界分析,其中条件时态网络从动态过渡到动态-一致。

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