Measure-Free Conditioning, Probability and Non-Monotonic Reasoning
Proceedings of the Eleventh International Joint Conference on Artificial Intelligence. Commonsense Reasoning. Pages 1110-1113.
Abstract
Recent results in the foundations of probability theory indicate that a conditional probability can be viewed as a probability attached to a mathematical entity called a measure-free conditional. Such a measure-free conditional can receive a semantics in terms of a trivalent logic and logical operations are defined on conditionals in terms of truth-tables. It is shown that these results can be useful to justify Cox's axiomatic framework for probability as well as its application to other theories of uncertainty (Shafer's plausibility functions and Zadeh's possibility measures). Moreover it is shown that measure-free conditionals have the properties of well-behaved non-monotonic inference rules.
@inproceedings{ijcai1989p178,
title = {Measure-Free Conditioning, Probability and Non-Monotonic Reasoning},
author = {Dubois, Didier and Prade, Henri},
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 = {1110--1113},
year = {1989},
month = {8},
note = {Commonsense Reasoning},
url = {https://ijcai.org/proceedings/1989/178},
}
TY - CPAPER TI - Measure-Free Conditioning, Probability and Non-Monotonic Reasoning AU - Dubois, Didier AU - Prade, Henri T2 - Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, IJCAI-89 PB - International Joint Conferences on Artificial Intelligence PY - 1989 SP - 1110 EP - 1113 UR - https://ijcai.org/proceedings/1989/178 ER -Copied
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