Abstract
This paper introduces a framework for relevant belief revision. We represent agent’s beliefs in prime implicants and express agent’s preference on beliefs as a pre-order over terms. We define a belief revision operator via minimising the change of the prime implicants of the existing beliefs and the incoming information with respect to agent’s preferences. We show that such a belief revision operator satisfies Katsuno and Mendelzon’s postulates for belief revision as well as Parikh’s postulate for relevant revision. This paper demonstrates a natural way to identify relevance of beliefs and an implementation of Parikh’s relevant belief revision.
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Perrussel, L., Marchi, J., Zhang, D. (2010). Characterizing Relevant Belief Revision Operators. In: Li, J. (eds) AI 2010: Advances in Artificial Intelligence. AI 2010. Lecture Notes in Computer Science(), vol 6464. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17432-2_5
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DOI: https://doi.org/10.1007/978-3-642-17432-2_5
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