Temporal Reasoning with Qualitative and Quantitative Information About Points and Durations

Abstract

A duration is known as a time distance between two point events. This relationship has recently been formalized as the point duration network (PDN) in (Navarrete & Marin 1997). However, only the qualitative information about points and durations was considered. This paper presents an augmented point duration network (APDN) to represent both qualitative and quantitative information about point events. We further extend APDN to capture quantitative information about durations. We propose algorithms to solve reasoning tasks such as determining satisfiability of the network, and finding a consistent scenario with minimal domains. Thus, we present an expressively richer framework than the existing ones to handle both qualitative and quantitative information about points as well as durations. Introduction Temporal knowledge can be classified into two main categories: qualitative and quantitative (or metric) information. Relationships between events (e.g., Fred arrived at wo...

Cite

Text

Wetprasit and Sattar. "Temporal Reasoning with Qualitative and Quantitative Information About Points and Durations." AAAI Conference on Artificial Intelligence, 1998.

Markdown

[Wetprasit and Sattar. "Temporal Reasoning with Qualitative and Quantitative Information About Points and Durations." AAAI Conference on Artificial Intelligence, 1998.](https://mlanthology.org/aaai/1998/wetprasit1998aaai-temporal/)

BibTeX

@inproceedings{wetprasit1998aaai-temporal,
  title     = {{Temporal Reasoning with Qualitative and Quantitative Information About Points and Durations}},
  author    = {Wetprasit, Rattana and Sattar, Abdul},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {1998},
  pages     = {656-663},
  url       = {https://mlanthology.org/aaai/1998/wetprasit1998aaai-temporal/}
}