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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 36 / No. 5: AAAI-22 Technical Tracks 5

Using Conditional Independence for Belief Revision

February 1, 2023

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Authors

Matthew James Lynn

Simon Fraser University


James P. Delgrande

Simon Fraser University


Pavlos Peppas

University of Patras


DOI:

10.1609/aaai.v36i5.20524


Abstract:

We present an approach to incorporating qualitative assertions of conditional irrelevance into belief revision, in order to address the limitations of existing work which considers only unconditional irrelevance. These assertions serve to enforce the requirement of minimal change to existing beliefs, while also suggesting a route to reducing the computational cost of belief revision by excluding irrelevant beliefs from consideration. In our approach, a knowledge engineer specifies a collection of multivalued dependencies that encode domain-dependent assertions of conditional irrelevance in the knowledge base. We consider these as capturing properties of the underlying domain which should be taken into account during belief revision. We introduce two related notions of what it means for a multivalued dependency to be taken into account by a belief revision operator: partial and full compliance. We provide characterisations of partially and fully compliant belief revision operators in terms of semantic conditions on their associated faithful rankings. Using these characterisations, we show that the constraints for partially and fully compliant belief revision operators are compatible with the AGM postulates. Finally, we compare our approach to existing work on unconditional irrelevance in belief revision.

Topics: AAAI

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HOW TO CITE:

Matthew James Lynn||James P. Delgrande||Pavlos Peppas Using Conditional Independence for Belief Revision Proceedings of the AAAI Conference on Artificial Intelligence (2022) 5809-5816.

Matthew James Lynn||James P. Delgrande||Pavlos Peppas Using Conditional Independence for Belief Revision AAAI 2022, 5809-5816.

Matthew James Lynn||James P. Delgrande||Pavlos Peppas (2022). Using Conditional Independence for Belief Revision. Proceedings of the AAAI Conference on Artificial Intelligence, 5809-5816.

Matthew James Lynn||James P. Delgrande||Pavlos Peppas. Using Conditional Independence for Belief Revision. Proceedings of the AAAI Conference on Artificial Intelligence 2022 p.5809-5816.

Matthew James Lynn||James P. Delgrande||Pavlos Peppas. 2022. Using Conditional Independence for Belief Revision. "Proceedings of the AAAI Conference on Artificial Intelligence". 5809-5816.

Matthew James Lynn||James P. Delgrande||Pavlos Peppas. (2022) "Using Conditional Independence for Belief Revision", Proceedings of the AAAI Conference on Artificial Intelligence, p.5809-5816

Matthew James Lynn||James P. Delgrande||Pavlos Peppas, "Using Conditional Independence for Belief Revision", AAAI, p.5809-5816, 2022.

Matthew James Lynn||James P. Delgrande||Pavlos Peppas. "Using Conditional Independence for Belief Revision". Proceedings of the AAAI Conference on Artificial Intelligence, 2022, p.5809-5816.

Matthew James Lynn||James P. Delgrande||Pavlos Peppas. "Using Conditional Independence for Belief Revision". Proceedings of the AAAI Conference on Artificial Intelligence, (2022): 5809-5816.

Matthew James Lynn||James P. Delgrande||Pavlos Peppas. Using Conditional Independence for Belief Revision. AAAI[Internet]. 2022[cited 2023]; 5809-5816.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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