Parallel Formulation of Evidential-Reasoning Theories
Proceedings of the Ninth International Joint Conference on Artificial Intelligence. Expert Systems. Pages 321-326.
Abstract
There ia no general consensus on bow best to attack evidential-reasoning (ER) problems, paniculady in expert-ayatem applications. Several approaches have evolved, but they have their roots in divene fields, eucb u etatiatice and pbiloeopby, and have neither a common terminology nor a common eet of ueumptiona. The research reported here provides two useful results. Firat, it etructures the evidential-reasoning problem in a general paradigm robust enough to be of practical uee in design and construction of expert eyateme. Second, it ueee tbia paradigm to formulate five important theoretical approaches in a parallel fubion in order to identify key ueumptione, eimilaritles, and differences. The five approaches diecueeed are clueical Bays, convex Bayee, Dempeter-Sbafer, Kyburg, and poeeibility.
@inproceedings{ijcai1985p61,
title = {Parallel Formulation of Evidential-Reasoning Theories},
author = {Thompson, Terence R.},
booktitle = {Proceedings of the Ninth International Joint Conference on
Artificial Intelligence, {IJCAI-85}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Aravind Joshi},
pages = {321--326},
year = {1985},
note = {Expert Systems},
url = {https://ijcai.org/proceedings/1985/61},
}
TY - CPAPER TI - Parallel Formulation of Evidential-Reasoning Theories AU - Thompson, Terence R. T2 - Proceedings of the Ninth International Joint Conference on Artificial Intelligence, IJCAI-85 PB - International Joint Conferences on Artificial Intelligence PY - 1985 SP - 321 EP - 326 UR - https://ijcai.org/proceedings/1985/61 ER -Copied
Machine-readable versions of this paper, for tools and AI agents:
