Belief revision: A critique [Book Review]
David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Journal of Logic, Language and Information 8 (4):401-420 (1999)
We examine carefully the rationale underlying the approaches to belief change taken in the literature, and highlight what we view as methodological problems. We argue that to study belief change carefully, we must be quite explicit about the ontology or scenario underlying the belief change process. This is something that has been missing in previous work, with its focus on postulates. Our analysis shows that we must pay particular attention to two issues that have often been taken for granted: the first is how we model the agent's epistemic state. (Do we use a set of beliefs, or a richer structure, such as an ordering on worlds? And if we use a set of beliefs, in what language are these beliefs are expressed?) We show that even postulates that have been called beyond controversy are unreasonable when the agent's beliefs include beliefs about her own epistemic state as well as the external world. The second is the status of observations. (Are observations known to be true, or just believed? In the latter case, how firm is the belief?) Issues regarding the status of observations arise particularly when we consider iterated belief revision, and we must confront the possibility of revising by and then by ¬.
|Keywords||AGM postulates belief revision iterated revision|
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Citations of this work BETA
Robert Stalnaker (2009). Iterated Belief Revision. Erkenntnis 70 (2):189 - 209.
Giacomo Bonanno (2005). A Simple Modal Logic for Belief Revision. Synthese 147 (2):193 - 228.
Giacomo Bonanno (2012). Belief Change in Branching Time: AGM-Consistency and Iterated Revision. [REVIEW] Journal of Philosophical Logic 41 (1):201-236.
Eduardo Fermé & Sven Ove Hansson (2011). AGM 25 Years: Twenty-Five Years of Research in Belief Change. Journal of Philosophical Logic 40 (2):295 - 331.
Raghav Ramachandran, Arthur Ramer & Abhaya C. Nayak (2012). Probabilistic Belief Contraction. Minds and Machines 22 (4):325-351.
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