Foundations of Probabilistic Logic
Proceedings of the Tenth International Joint Conference on Artificial Intelligence. Reasoning. Pages 939-940.
Abstract
We formalize a mathematical approach to probabilistic logic for zero-order logic and derive new inequalities that are necessary and sufficient for consistent probability assignments to propositions. We prove that a complete theory of probabilistic logic requires the a priori assignment of 21t-l probabilities for a system with k basic propositions. We also show that a ·proposal due to Cheeseman, namely, to regard measures of confidence in knowledge systems as expectations that are conditioned on unknown distributions, does not work in general. We demonstrate this by showing that several certainty measures proposed for expert systems are not consistent with the derived inequalities for probabilistic logiCs.
@inproceedings{ijcai1987p193,
title = {Foundations of Probabilistic Logic},
author = {Guggenheimer, H. and Freedman, R. S.},
booktitle = {Proceedings of the Tenth International Joint Conference on
Artificial Intelligence, {IJCAI-87}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {John McDermott},
pages = {939--940},
year = {1987},
note = {Reasoning},
url = {https://ijcai.org/proceedings/1987/193},
}
TY - CPAPER TI - Foundations of Probabilistic Logic AU - Guggenheimer, H. AU - Freedman, R. S. T2 - Proceedings of the Tenth International Joint Conference on Artificial Intelligence, IJCAI-87 PB - International Joint Conferences on Artificial Intelligence PY - 1987 SP - 939 EP - 940 UR - https://ijcai.org/proceedings/1987/193 ER -Copied
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