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Rough Belief Change

Authors: Mohua Banerjee;

Rough Belief Change

Abstract

The article aims at re-visiting the notion of rough truth proposed by Pawlak in 1987 [15] and investigating some of its ‘logical’ consequences. We focus on the formal deductive apparatus $\cal L_R$, that is sound and complete with respect to a semantics based on rough truth. $\cal L_R$ turns out to be equivalent to the paraconsistent logic J due to Jaśkowski. A significant feature of rough truth is that, a proposition and its negation may well be roughly true together. Thus, in [5], rough consistency was introduced. Completeness of $\cal L_R$ is proved with the help of this notion of consistency. The properties of $\cal L_R$ motivate us to use it for a proposal of rough belief change. During change, the operative constraints on a system of beliefs are that of rough consistency preservation and deductive closure with respect to $\cal L_R$. Following the AGM [1] line, eight basic postulates for defining rough revision and contraction functions are presented. Interrelationships of these functions are also proved. The proposal is, therefore, an example of paraconsistent belief change.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
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