Title of article :
Parallel belief revision: Revising by sets of formulas Original Research Article
Author/Authors :
James Delgrande، نويسنده , , Yi Jin، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2012
Pages :
23
From page :
2223
To page :
2245
Abstract :
The area of belief revision studies how a rational agent may incorporate new information about a domain into its belief corpus. An agent is characterised by a belief state K, and receives a new item of information α which is to be included among its set of beliefs. Revision then is a function from a belief state and a formula to a new belief state. We propose here a more general framework for belief revision, in which revision is a function from a belief state and a finite set of formulas to a new belief state. In particular, we distinguish revision by the set image from the set image. This seemingly innocuous change has significant ramifications with respect to iterated belief revision. A problem in approaches to iterated belief revision is that, after first revising by a formula and then by a formula that is inconsistent with the first formula, all information in the original formula is lost. This problem is avoided here in that, in revising by a set of formulas S, the resulting belief state contains not just the information that members of S are believed to be true, but also the counterfactual supposition that if some members of S were later believed to be false, then the remaining members would nonetheless still be believed to be true. Thus if some members of S were in fact later believed to be false, then the other elements of S would still be believed to be true. Hence, we provide a more nuanced approach to belief revision. The general approach, which we call parallel belief revision, is independent of extant approaches to iterated revision. We present first a basic approach to parallel belief revision. Following this we combine the basic approach with an approach due to Jin and Thielscher for iterated revision. Postulates and semantic conditions characterising these approaches are given, and representation results provided. We conclude with a discussion of the possible ramifications of this approach in belief revision in general.
Keywords :
Belief change , Iterated belief revision , Knowledge representation and reasoning , Epistemic states
Journal title :
Artificial Intelligence
Serial Year :
2012
Journal title :
Artificial Intelligence
Record number :
1207887
Link To Document :
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