Temporal Decision Trees or the lazy ECU vindicated
Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence. .
Abstract
The automatic generation of diagnostic decision trees from qualitative models is a reasonable compromise between the advantages of using a modelbased approach in technical domains and the constraints imposed by on-board applications. In this paper we extend the approach to deal with temporal information. We introduce a notion of temporal diagnostic decision tree, in which nodes have a temporal label providing temporal constraints on the observations, and we present an algorithm for compiling such trees from a model-based diagnostic system.
@inproceedings{ijcai2001p76,
title = {Temporal Decision Trees or the lazy ECU vindicated},
author = {Console, Luca and Picardi, Claudia and Dupré, Daniele Theseider},
booktitle = {Proceedings of the Seventeenth International Joint Conference on
Artificial Intelligence, {IJCAI-01}},
publisher = {International Joint Conferences on Artificial Intelligence},
year = {2001},
url = {https://ijcai.org/proceedings/2001/76},
}
TY - CPAPER TI - Temporal Decision Trees or the lazy ECU vindicated AU - Console, Luca AU - Picardi, Claudia AU - Dupré, Daniele Theseider T2 - Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, IJCAI-01 PB - International Joint Conferences on Artificial Intelligence PY - 2001 UR - https://ijcai.org/proceedings/2001/76 ER -Copied
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