Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10320336 | Artificial Intelligence | 2005 | 24 Pages |
Abstract
We revisit the problem of revising probabilistic beliefs using uncertain evidence, and report results on several major issues relating to this problem: how should one specify uncertain evidence? How should one revise a probability distribution? How should one interpret informal evidential statements? Should, and do, iterated belief revisions commute? And what guarantees can be offered on the amount of belief change induced by a particular 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.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Hei Chan, Adnan Darwiche,