Hybrid SAT-Based Consistency Checking Algorithms for Simple Temporal Networks with Decisions

Time Pub Date : 2019-08-02 DOI:10.4230/LIPIcs.TIME.2019.16
Matteo Zavatteri, Combi Carlo, Romeo Rizzi, L. Viganò
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引用次数: 8

Abstract

A Simple Temporal Network (STN) consists of time points modeling temporal events and constraints modeling the minimal and maximal temporal distance between them. A Simple Temporal Network with Decisions (STND) extends an STN by adding decision time points to model temporal plans with decisions. A decision time point is a special kind of time point that once executed allows for deciding a truth value for an associated Boolean proposition. Furthermore, STNDs label time points and constraints by conjunctions of literals saying for which scenarios (i.e., complete truth value assignments to the propositions) they are relevant. Thus, an STND models a family of STNs each obtained as a projection of the initial STND onto a scenario. An STND is consistent if there exists a consistent scenario (i.e., a scenario such that the corresponding STN projection is consistent). Recently, a hybrid SAT-based consistency checking algorithm (HSCC) was proposed to check the consistency of an STND. Unfortunately, that approach lacks experimental evaluation and does not allow for the synthesis of all consistent scenarios. In this paper, we propose an incremental HSCC algorithm for STNDs that (i) is faster than the previous one and (ii) allows for the synthesis of all consistent scenarios and related early execution schedules (offline temporal planning). Then, we carry out an experimental evaluation with Kappa, a tool that we developed for STNDs. Finally, we prove that STNDs and disjunctive temporal networks (DTNs) are equivalent. 2012 ACM Subject Classification Theory of computation → Timed and hybrid models; Computing methodologies → Temporal reasoning; Computing methodologies → Planning and scheduling; Mathematics of computing → Graph algorithms; Hardware → Theorem proving and SAT solving
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具有决策的简单时态网络的混合sat一致性检验算法
简单时间网络(STN)由建模时间事件的时间点和建模它们之间的最小和最大时间距离的约束组成。具有决策的简单时间网络(STND)通过添加决策时间点来对具有决策的时间计划进行建模,从而扩展了STN。决策时间点是一种特殊的时间点,一旦执行,就可以决定相关布尔命题的真值。此外,STND通过文字的连词来标记时间点和约束,说明它们与哪些场景(即命题的完全真值分配)相关。因此,STND对STN家族进行建模,每个STN都是作为初始STND到场景上的投影而获得的。如果存在一致的场景(即,使得对应的STN投影一致的场景),则STND是一致的。最近,提出了一种基于SAT的混合一致性检查算法(HSCC)来检查STND的一致性。不幸的是,这种方法缺乏实验性评估,无法综合所有一致的情景。在本文中,我们为STND提出了一种增量HSCC算法,该算法(i)比以前的算法更快,并且(ii)允许综合所有一致的场景和相关的早期执行时间表(离线时间规划)。然后,我们使用Kappa进行了实验评估,Kappa是我们为STND开发的工具。最后,我们证明了STND和析取时间网络是等价的。2012 ACM学科分类计算理论→ 定时和混合动力车型;计算方法→ 时间推理;计算方法→ 计划和进度安排;计算数学→ 图形算法;硬件→ 定理证明与SAT求解
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