TY - JOUR
T1 - Relevant minimal change in belief update
AU - Perrussel, Laurent
AU - Marchi, Jerusa
AU - Thévenin, Jean-Marc
AU - Zhang, Dongmo
PY - 2012
Y1 - 2012
N2 - The notion of relevance was introduced by Parikh in the belief revision field for handling minimal change. It prevents the loss of beliefs that do not have connections with the epistemic input. But, the problem of minimal change and relevance is still an open issue in belief update. In this paper, a new framework for handling minimal change and relevance in the context of belief update is introduced. This framework goes beyond relevance in Parikh’s sense and enforces minimal change by first rewriting the Katzuno-Mendelzon postulates for belief update and second by introducing a new relevance postulate. We show that relevant minimal change can be characterized by setting agent’s preferences on beliefs where preferences are indexed by subsets of models of the belief set. Each subset represents a prime implicant of the belief set and thus stresses the key propositional symbols for representing the belief set.
AB - The notion of relevance was introduced by Parikh in the belief revision field for handling minimal change. It prevents the loss of beliefs that do not have connections with the epistemic input. But, the problem of minimal change and relevance is still an open issue in belief update. In this paper, a new framework for handling minimal change and relevance in the context of belief update is introduced. This framework goes beyond relevance in Parikh’s sense and enforces minimal change by first rewriting the Katzuno-Mendelzon postulates for belief update and second by introducing a new relevance postulate. We show that relevant minimal change can be characterized by setting agent’s preferences on beliefs where preferences are indexed by subsets of models of the belief set. Each subset represents a prime implicant of the belief set and thus stresses the key propositional symbols for representing the belief set.
KW - belief revision
KW - prime implicants
KW - artificial intelligence
UR - http://handle.uws.edu.au:8081/1959.7/520455
U2 - 10.1007/978-3-642-33353-8_26
DO - 10.1007/978-3-642-33353-8_26
M3 - Article
SN - 0302-9743
VL - 7519
SP - 333
EP - 345
JO - Lecture Notes in Computer Science
JF - Lecture Notes in Computer Science
ER -