定时轨迹上的公制时态均衡逻辑

IF 1.4 2区 数学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
ARVID BECKER, PEDRO CABALAR, MARTÍN DIÉGUEZ, TORSTEN SCHAUB, ANNA SCHUHMANN
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引用次数: 0

摘要

在基于线性时间的答案集编程(ASP)的时间扩展中,动态系统的行为是通过状态序列来捕捉的。虽然这种表示法反映了它们的相对顺序,但却抽象掉了与每个状态相关的具体时间。然而,时间约束在很多应用中都很重要,例如在计划和调度同时进行的情况下。为了解决这个问题,我们开发了线性时间时间平衡逻辑的度量扩展,其中时间运算符受自然数间隔的约束。由此产生的度量均衡逻辑(MEL)为基于 ASP 的方法提供了基础,可用于指定定性和定量动态约束。为此,我们定义了公因子公式到一元一阶公式的翻译,并分别给出了它们在 MEL 和一元量化均衡逻辑中的模型之间的对应关系。有趣的是,我们的翻译为 ASP 模差约束的实现提供了蓝图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Metric Temporal Equilibrium Logic over Timed Traces
In temporal extensions of answer set programming (ASP) based on linear time, the behavior of dynamic systems is captured by sequences of states. While this representation reflects their relative order, it abstracts away the specific times associated with each state. However, timing constraints are important in many applications like, for instance, when planning and scheduling go hand in hand. We address this by developing a metric extension of linear-time temporal equilibrium logic, in which temporal operators are constrained by intervals over natural numbers. The resulting Metric Equilibrium Logic (MEL) provides the foundation of an ASP-based approach for specifying qualitative and quantitative dynamic constraints. To this end, we define a translation of metric formulas into monadic first-order formulas and give a correspondence between their models in MEL and Monadic Quantified Equilibrium Logic, respectively. Interestingly, our translation provides a blue print for implementation in terms of ASP modulo difference constraints.
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来源期刊
Theory and Practice of Logic Programming
Theory and Practice of Logic Programming 工程技术-计算机:理论方法
CiteScore
4.50
自引率
21.40%
发文量
40
审稿时长
>12 weeks
期刊介绍: Theory and Practice of Logic Programming emphasises both the theory and practice of logic programming. Logic programming applies to all areas of artificial intelligence and computer science and is fundamental to them. Among the topics covered are AI applications that use logic programming, logic programming methodologies, specification, analysis and verification of systems, inductive logic programming, multi-relational data mining, natural language processing, knowledge representation, non-monotonic reasoning, semantic web reasoning, databases, implementations and architectures and constraint logic programming.
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