IJCAI 2022poster9 citations

Conditional Independence for Iterated Belief Revision

Gabriele Kern-Isberner, Jesse Heyninck, Christoph Beierle

Abstract

Conditional independence is a crucial concept for efficient probabilistic reasoning. For symbolic and qualitative reasoning, however, it has played only a minor role. Recently, Lynn, Delgrande, and Peppas have considered conditional independence in terms of syntactic multivalued dependencies. In this paper, we define conditional independence as a semantic property of epistemic states and present axioms for iterated belief revision operators to obey conditional independence in general. We show that c-revisions for ranking functions satisfy these axioms, and exploit the relevance of these results for iterated belief revision in general.

Knowledge Representation and Reasoning: Belief ChangeKnowledge Representation and Reasoning: Non-monotonic ReasoningKnowledge Representation and Reasoning: Qualitative, Geometric, Spatial, Temporal ReasoningKnowledge Representation and Reasoning: Reasoning about Knowledge and Belief
BibTeX
@inproceedings{ijcai2022p373,
  title     = {Conditional Independence for Iterated Belief Revision},
  author    = {Kern-Isberner, Gabriele and Heyninck, Jesse and Beierle, Christoph},
  booktitle = {Proceedings of the Thirty-First International Joint Conference on
               Artificial Intelligence, {IJCAI-22}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Lud De Raedt},
  pages     = {2690--2696},
  year      = {2022},
  month     = {7},
  note      = {Main Track},
  doi       = {10.24963/ijcai.2022/373},
  url       = {https://doi.org/10.24963/ijcai.2022/373},
}
Conditional Independence for Iterated Belief Revision · IJCAI 2022