A Semantics for Probabilistic Quantifier-Free First-Order Languages, with Particular Application to Story Understanding
Proceedings of the Eleventh International Joint Conference on Artificial Intelligence. Commonsense Reasoning. Pages 1074-1078.
Abstract
We present a semantics for interpreting probabilistic statements expressed in a first-order quantifier-free language. We show how this semantics places constraints on the probabilities which can be associated with such statements. We then consider its use in the area of story understanding. We show that for at least simple models of stories (equivalent to the script/plan models) there are ways to specify reasonably good probabilities. Lastly, we show that while the semantics dictates seemingly implausibly low prior probabilities for equality statements, once they are conditioned by an assumption of spatio-temporal locality of observation the probabilities become "reasonable."
@inproceedings{ijcai1989p172,
title = {A Semantics for Probabilistic Quantifier-Free First-Order Languages, with Particular Application to Story Understanding},
author = {Charniak, Eugene and Goldman, Robert P.},
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 = {1074--1078},
year = {1989},
month = {8},
note = {Commonsense Reasoning},
url = {https://ijcai.org/proceedings/1989/172},
}
TY - CPAPER TI - A Semantics for Probabilistic Quantifier-Free First-Order Languages, with Particular Application to Story Understanding AU - Charniak, Eugene AU - Goldman, Robert P. T2 - Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, IJCAI-89 PB - International Joint Conferences on Artificial Intelligence PY - 1989 SP - 1074 EP - 1078 UR - https://ijcai.org/proceedings/1989/172 ER -Copied
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