Computing Effect-to-Cause/Cause-to-Effect Diagnoses Within NdL
Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence. Neural Networks. Pages 1332-1337.
Abstract
The computation of effect-to-cause (called also deductive) diagnoses is rather straighforward whatever the considered framework- logical, neural , etc. This paper focuses on the computation of cause-to-effect (called also abductive) diagnoses. Ultimately, we show how mechanize the abduction within a neural framework and illustrate our mechanization by illustrati ve examples. Finally, we present instructive lessons learnt from our experimentation with NdL (a Neural Diagnosis Laboratory) and point out the innovative features of this work as well as the important issues deserving further investigations.
@inproceedings{ijcai1993p184,
title = {Computing Effect-to-Cause/Cause-to-Effect Diagnoses Within NdL},
author = {Ayeb, Béchir el and Wang, Shengrui},
booktitle = {Proceedings of the Thirteenth International Joint Conference on
Artificial Intelligence, {IJCAI-93}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Ruzena Bajcsy},
pages = {1332--1337},
year = {1993},
note = {Neural Networks},
url = {https://ijcai.org/proceedings/1993/184},
}
TY - CPAPER TI - Computing Effect-to-Cause/Cause-to-Effect Diagnoses Within NdL AU - Ayeb, Béchir el AU - Wang, Shengrui T2 - Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence, IJCAI-93 PB - International Joint Conferences on Artificial Intelligence PY - 1993 SP - 1332 EP - 1337 UR - https://ijcai.org/proceedings/1993/184 ER -Copied
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