Belief Functions and Default Reasoning
Abstract
We present a new approach to dealing with default information based on the theory of belief functions. Our semantic structures, inspired by Adams' epsilon-semantics, are epsilon-belief assignments, where values committed to focal elements are either close to 0 or close to 1. We define two systems based on these structures, and relate them to other non-monotonic systems presented in the literature. We show that our second system correctly addresses the well-known problems of specificity, irrelevance, blocking of inheritance, ambiguity, and redundancy.
Cite
Text
Benferhat et al. "Belief Functions and Default Reasoning." Conference on Uncertainty in Artificial Intelligence, 1995. doi:10.1016/S0004-3702(00)00041-2Markdown
[Benferhat et al. "Belief Functions and Default Reasoning." Conference on Uncertainty in Artificial Intelligence, 1995.](https://mlanthology.org/uai/1995/benferhat1995uai-belief/) doi:10.1016/S0004-3702(00)00041-2BibTeX
@inproceedings{benferhat1995uai-belief,
title = {{Belief Functions and Default Reasoning}},
author = {Benferhat, Salem and Saffiotti, Alessandro and Smets, Philippe},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {1995},
pages = {19-26},
doi = {10.1016/S0004-3702(00)00041-2},
url = {https://mlanthology.org/uai/1995/benferhat1995uai-belief/}
}