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Cited by 269

The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.

Time and time again: The many ways to represent time

Allen, James F.·1991·International Journal of Intelligent Systems

Abstract

One of the most crucial problems in any computer system that involves representing the world is the representation of time. This includes applications such as databases, simulation, expert systems, and applications of Artificial Intelligence in general. In this brief article, I will give a survey of the basic techniques available for representing time, and then talk about temporal reasoning in a general setting as needed in AI applications. Quite different representations of time are usable depending on the assumptions that can be made about the temporal information to be represented. the most crucial issue is the degree of certainty one can assume. Can one assume that a timestamp can be assigned to each event, or barring that, that the events are fully ordered? Or can we only assume that a partial ordering of events is known? Can events be simultaneous? Can they overlap in time and yet not be simultaneous? If they are not instaneous, do we know the durations of events? Different answers to each of these questions allow very different representations of time.

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Metadata

Authors
Allen, J. F.
Venue
International Journal of Intelligent Systems
Published
1991-07
Volume
6
Issue
4
Pages
341-355
ISSN
  • 0884-8173 (ISSN-L)
  • 1098-111X
OpenAlex
W1987118521
Cited by
269
References
15
FWCI
3.34
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Time and time again: The many ways to represent time. https://app.cochat.ai/papers/10.1002/int.4550060403
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Allen, J. F. (1991). Time and time again: The many ways to represent time. International Journal of Intelligent Systems. https://doi.org/10.1002/int.4550060403

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.