Temporal Matching: Recognizing Dynamic Situations from Discrete Measurements
Proceedings of the Eleventh International Joint Conference on Artificial Intelligence. Knowledge Representation. Pages 1255-1259.
Abstract
The converse problem of measurement interpretation is event recognition. In situations which are characterized by a specific order of events, a single snapshot is not sufficient to recognize an event. Instead one has to plan a measurement sequence that consists of observations at more than one time point. In this paper we present an algorithm for planning such an observation sequence based on the specification of the event and discuss the problem of giving a meaningful definition of a 'successful match of a measurement sequence against a situation description'.
@inproceedings{ijcai1989p201,
title = {Temporal Matching: Recognizing Dynamic Situations from Discrete Measurements},
author = {Nökel, Klaus},
booktitle = {Proceedings of the Eleventh International Joint Conference on
Artificial Intelligence, {IJCAI-89}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {N. S. Sridharan},
pages = {1255--1259},
year = {1989},
month = {8},
note = {Knowledge Representation},
url = {https://ijcai.org/proceedings/1989/201},
}
TY - CPAPER TI - Temporal Matching: Recognizing Dynamic Situations from Discrete Measurements AU - Nökel, Klaus T2 - Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, IJCAI-89 PB - International Joint Conferences on Artificial Intelligence PY - 1989 SP - 1255 EP - 1259 UR - https://ijcai.org/proceedings/1989/201 ER -Copied
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