Abstract
This chapter is devoted to logical models for reasoning from contradictory information. It deals with methods, such as argumentation, that refrain from giving up any piece of information (by contrast with revision, as discussed in chapter “Main Issues in Belief Revision, Belief Merging and Information Fusion” of this volume). The baseline is to get the best, resorting to various possibilities, from the available information in order to reason in the most sensible way despite contradictions.
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Notes
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- 2.
This ordering only depends on the stratum having the highest priority in which at least one formula has been removed for restoring consistency.
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This principle consists in keeping among the credulous consequences only those such that their negation is not credulously inferred (Benferhat et al. 1993b). This inference is said argumentative.
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Note that the Bo-preferred subbases are not presented here. Nevertheless all of them respect a common property: they contain the two formulae e and \(e \rightarrow b\) and so they entail e and b.
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There are plenty of other references.
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Amgoud, L., Besnard, P., Cayrol, C., Chatalic, P., Lagasquie-Schiex, MC. (2020). Argumentation and Inconsistency-Tolerant Reasoning. In: Marquis, P., Papini, O., Prade, H. (eds) A Guided Tour of Artificial Intelligence Research. Springer, Cham. https://doi.org/10.1007/978-3-030-06164-7_13
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