简单时间网络:时间表征和推理的实践基础(特邀演讲)

Time Pub Date : 2021-01-01 DOI:10.4230/LIPIcs.TIME.2021.1
Luke Hunsberger, Roberto Posenato
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引用次数: 2

摘要

自1991年首次引入简单时态网络(STNs)以来,已经有许多理论和算法的进步,使它们在各种各样的应用中都具有实用性。然而,大多数重要进展的介绍都分散在许多会议论文和期刊文章中。因此,即使是经验丰富的研究人员也很容易不知道可能对他们的工作产生积极影响的结果。在这次演讲中,我们将回顾关于STNs的最重要的结果,这些结果是为那些对将时间和时间约束管理纳入其项目感兴趣的人工智能研究人员提供的。2012 ACM主题分类计算方法→时间推理;计算理论→网络优化;计算理论→动态图算法;计算数学→图算法
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Simple Temporal Networks: A Practical Foundation for Temporal Representation and Reasoning (Invited Talk)
Since Simple Temporal Networks (STNs) were first introduced in 1991, there have been numerous theoretic and algorithmic advances that have made them practical for a wide variety of applications. However, the presentation of most of the important advances have been scattered across numerous conference papers and journal articles. As a result, it is too easy for even experienced researchers to be unaware of results that could positively impact their work. In this talk we review the most important results about STNs for researchers in Artificial Intelligence who are interested in incorporating the management of time and temporal constraints into their projects. 2012 ACM Subject Classification Computing methodologies → Temporal reasoning; Theory of computation → Network optimization; Theory of computation → Dynamic graph algorithms; Mathematics of computing → Graph algorithms
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