Non-Prioritized Ranked Belief Change |
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Authors: | Chopra Samir Ghose Aditya Meyer Thomas |
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Affiliation: | (1) Department of Computer and Information Science Brooklyn College of the City, University of New York, Brooklyn, NY 11210, USA;(2) Decision Systems Laboratory School of Information Technology and Computer Science, University of Wollongong, Wollongong, NSW, 2522, Australia;(3) National ICT Australia School of Computer Science & Engineering, University of New South Wales, NSW, 2052, Australia |
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Abstract: | Traditional accounts of belief change have been criticized for placing undue emphasis on the new belief provided as input. A recent proposal to address such issues is a framework for non-prioritized belief change based on default theories (Ghose and Goebel, 1998). A novel feature of this approach is the introduction of disbeliefs alongside beliefs which allows for a view of belief contraction as independently useful, instead of just being seen as an intermediate step in the process of belief revision. This approach is, however, restrictive in assuming a linear ordering of reliability on the received inputs. In this paper, we replace the linear ordering with a preference ranking on inputs from which a total preorder on inputs can be induced. This extension brings along with it the problem of dealing with inputs of equal rank. We provide a semantic solution to this problem which contains, as a special case, AGM belief change on closed theories. |
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Keywords: | belief change contraction non-monotonic inference |
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