Belief Change Based on Global Minimisation
Proceedings of the Twentieth International Joint Conference on Artificial Intelligence. Pages 2468-2472.
Abstract
A general framework for minimisation-based belief change is presented. A problem instance is made up of an undirected graph, where a formula is associated with each vertex. For example, vertices may represent spatial locations, points in time, or some other notion of locality. Information is shared between vertices via a process of minimisation over the graph. We give equivalent semantic and syntactic characterisations of this minimisation. We also show that this approach is general enough to capture existing minimisation-based approaches to belief merging, belief revision, and (temporal) extrapolation operators. While we focus on a set-theoretic notion of minimisation, we also consider other approaches, such as cardinality-based and priority-based minimisation.
@inproceedings{ijcai2007p397,
title = {Belief Change Based on Global Minimisation},
author = {Delgrande, James P. and Lang, Jérôme and Schaub, Torsten},
booktitle = {Proceedings of the Twentieth International Joint Conference on
Artificial Intelligence, {IJCAI-07}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Ramon López de Mántaras},
pages = {2468--2472},
year = {2007},
url = {https://ijcai.org/proceedings/2007/397},
}
TY - CPAPER TI - Belief Change Based on Global Minimisation AU - Delgrande, James P. AU - Lang, Jérôme AU - Schaub, Torsten T2 - Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07 PB - International Joint Conferences on Artificial Intelligence PY - 2007 SP - 2468 EP - 2472 UR - https://ijcai.org/proceedings/2007/397 ER -Copied
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