Computational and Physical Causality
Proceedings of the Twelfth International Joint Conference on Artificial Intelligence. Qualitative Reasoning. Pages 1171-1175.
Abstract
Causality plays an important role in qualitative reasoning about physical systems. In this paper we show that the bond-graph method can be fruitfully applied to represent and generate causal order on a formal basis. Both physical and computational aspects of bond-graph causality are discussed. In particular we show that it provides a firmer physical foundation for a causal order along the lines of Iwasaki and Simon. Bond-graph causality also generates more information than does the causal ordering theory, including better causal resolution, an improved definition of exogeneity in terms of parameters and sources, automatic checking of selfcontainment, and a more detailed, physical treatment of feedback.
@inproceedings{ijcai1991p172,
title = {Computational and Physical Causality},
author = {Top, Jan L. and Akkermans, Hans},
booktitle = {Proceedings of the Twelfth International Joint Conference on
Artificial Intelligence, {IJCAI-91}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {John Mylopoulos and Ray Reiter},
pages = {1171--1175},
year = {1991},
month = {8},
note = {Qualitative Reasoning},
url = {https://ijcai.org/proceedings/1991/172},
}
TY - CPAPER TI - Computational and Physical Causality AU - Top, Jan L. AU - Akkermans, Hans T2 - Proceedings of the Twelfth International Joint Conference on Artificial Intelligence, IJCAI-91 PB - International Joint Conferences on Artificial Intelligence PY - 1991 SP - 1171 EP - 1175 UR - https://ijcai.org/proceedings/1991/172 ER -Copied
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