Proceedings

On the Revision of Probabilistic Beliefs using Uncertain Evidence

Download BibTeX Cite

Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence. Pages 99-104.

Abstract

We revisit the problem of revising probabilistic beliefs using uncertain evidence, and report results on four major issues relating to this problem: How to specify uncertain evidence? How to revise a distribution? Should, and do, iterated belief revisions commute? And how to provide guarantees on the amount of belief change induced by a revision? Our discussion is focused on two main methods for probabilistic revision: Jeffrey's rule of probability kinematics and Pearl's method of virtual evidence, where we analyze and unify these methods from the perspective of the questions posed above.

Hei Chan, and Adnan Darwiche. 2003. On the Revision of Probabilistic Beliefs using Uncertain Evidence. In Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, IJCAI-03. IJCAI, 99–104. https://ijcai.org/proceedings/2003/14
Welcome Future Conferences AI Journal Division IJCAI Proceedings About IJCAI IJCAI Awards