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Efficient Temporal Reasoning Through Timegraphs

Alfonso Gerevini, Lenhart K. Schubert
IJCAI 1993 pp. 648-654
/ijcai/1993/gerevini1993ijcai-efficient/

Abstract

In this paper we address the problem of scalability in temporal reasoning. In particular, new algorithms for efficiently managing large sets of relations in the Point Algebra are provided. Our representation of time is based on timegraphs, graphs partitioned into a set of chains on which the search is supported by a rnetagraph data structure. The approach is an extension of the time representation proposed by Schubert, Taugher and Miller in the context of story comprehension. The algorithms presented in this work concern the construction of a timegraph from a given set of relations and are implemented in a temporal reasoning system called TG-II. Experimental results show that our approach is very efficient, especially when the given relations admit representation as a collection of chains connected by relatively few cross-chain links. 1

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Text

Gerevini and Schubert. "Efficient Temporal Reasoning Through Timegraphs." International Joint Conference on Artificial Intelligence, 1993.

Markdown

[Gerevini and Schubert. "Efficient Temporal Reasoning Through Timegraphs." International Joint Conference on Artificial Intelligence, 1993.](https://mlanthology.org/ijcai/1993/gerevini1993ijcai-efficient/)

BibTeX

@inproceedings{gerevini1993ijcai-efficient,
  title     = {{Efficient Temporal Reasoning Through Timegraphs}},
  author    = {Gerevini, Alfonso and Schubert, Lenhart K.},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {1993},
  pages     = {648-654},
  url       = {https://mlanthology.org/ijcai/1993/gerevini1993ijcai-efficient/}
}