Evidential Reasoning in Semantic Networks: A Formal Theory
Abstract
This paper presents an evidential approach to knowledge representation and inference wherein the principle of maximum entropy is applied to deal with uncertainty and incompleteness. It focuses on a restricted representation language - similar in expressive power to semantic network formalisms, and develops a formal theory of evidential inheritance within this language. The theory applies to a limited, but we think interesting, class of inheritance problems including those that involve exceptions and multiple inheritance hierarchies. The language and the accompanying evidential inference structure provide a natural treatment of defaults and conflicting information. The evidence combination rule proposed in this paper is incremental, commutative and associative and hence, shares most of the attractive features of the Dempster-Shafer evidence combination rule. Furthermore, it is demonstrably better than the Dempster-Shafer rule in the context of the problems addressed in this paper. The resulting theory can be implemented as a highly parallel (connectionist) network made up of active elements that can solve inheritance problems in time proportional to the depth of the conceptual hierarchy.
Cite
Text
Shastri and Feldman. "Evidential Reasoning in Semantic Networks: A Formal Theory." International Joint Conference on Artificial Intelligence, 1985.Markdown
[Shastri and Feldman. "Evidential Reasoning in Semantic Networks: A Formal Theory." International Joint Conference on Artificial Intelligence, 1985.](https://mlanthology.org/ijcai/1985/shastri1985ijcai-evidential/)BibTeX
@inproceedings{shastri1985ijcai-evidential,
title = {{Evidential Reasoning in Semantic Networks: A Formal Theory}},
author = {Shastri, Lokendra and Feldman, Jerome A.},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {1985},
pages = {465-474},
url = {https://mlanthology.org/ijcai/1985/shastri1985ijcai-evidential/}
}