A Theory of Diagnosis for Incomplete Causal Models
Proceedings of the Eleventh International Joint Conference on Artificial Intelligence. Knowledge Representation. Pages 1311-1316.
Abstract
One of the problems of the recent approaches to problem solving based on deep knowledge is the lack of a formal treatment of incomplete knowledge. However, dealing with incomplete models is fundamental to many realworld domains. In this paper we propose a formal theory of causal diagnostic reasoning, dealing with different forms of incompleteness both in the general causal knowledge (missing or abstracted knowledge) and in the data describing a specific case under examination. Different forms of nonmonotonic reasoning (hypothetical and circumscriptive reasoning) are used in order to draw and confirm Conclusions from incomplete knowledge. Multiple fault solutions are treated in a natural way and parsimony criteria are used to rank alternative solutions.
@inproceedings{ijcai1989p210,
title = {A Theory of Diagnosis for Incomplete Causal Models},
author = {Console, Luca and Dupré, Daniele Theseider and Torasso, Pietro},
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 = {1311--1316},
year = {1989},
month = {8},
note = {Knowledge Representation},
url = {https://ijcai.org/proceedings/1989/210},
}
TY - CPAPER TI - A Theory of Diagnosis for Incomplete Causal Models AU - Console, Luca AU - Dupré, Daniele Theseider AU - Torasso, Pietro T2 - Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, IJCAI-89 PB - International Joint Conferences on Artificial Intelligence PY - 1989 SP - 1311 EP - 1316 UR - https://ijcai.org/proceedings/1989/210 ER -Copied
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