References of "International Journal of Approximate Reasoning"
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See detailGeneralized Information Theory for Hints
Ryan, Peter UL; Pouly, Marc; Kohlas, Juerg

in International Journal of Approximate Reasoning (2013), 54(1), 228-251

This paper develops a new uncertainty measure for the theory of hints that complies with the established semantics of statistical information theory and further satisfies all classical requirements for ... [more ▼]

This paper develops a new uncertainty measure for the theory of hints that complies with the established semantics of statistical information theory and further satisfies all classical requirements for such a measure imposed in the literature. The proposed functional decomposes into conversant uncertainty measures and therefore discloses a new interpretation of the latters as well. By abstracting to equivalence classes of hints we transport the new measure to mass functions in Dempster-Shafer theory and analyse its relationship with the aggregate uncertainty, which currently is the only known functional for the Dempster-Shafer theory of evidence that satisfies the same set of properties. Moreover, the perspective of hints reveals that the standard independence notion in Dempster-Shafer theory called non-interactivity corresponds to an amalgamation of probabilistic independence and qualitative independence between frames of discernment. All results in this paper are developed for arbitrary families of compatible frames generalizing the very specialized multi-variate systems that are usually studied in information theory. [less ▲]

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See detailPreference-based argumentation: Arguments supporting multiple values
Kaci, Souhila; van der Torre, Leon UL

in International Journal of Approximate Reasoning (2008), 48(3), 730751

In preference-based argumentation theory, an argument may be preferred to another one when, for example, it is more specific, its beliefs have a higher probability or certainty, or it promotes a higher ... [more ▼]

In preference-based argumentation theory, an argument may be preferred to another one when, for example, it is more specific, its beliefs have a higher probability or certainty, or it promotes a higher value. In this paper we generalize Bench-Capon’s value-based argumentation theory such that arguments can promote multiple values, and preferences among values or arguments can be specified in various ways. We assume in addition that there is default knowledge about the preferences over the arguments, and we use an algorithm to derive the most likely preference order. In particular, we show how to use non-monotonic preference reasoning to compute preferences among arguments, and subsequently the acceptable arguments, from preferences among values. We show also how the preference ordering can be used to optimize the algorithm to construct the grounded extension by proceeding from most to least preferred arguments. [less ▲]

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