Abstract
In many fields of automated information processing it becomes crucial to consider imprecise, uncertain or inconsistent pieces of information. Therefore, integrating uncertainty factors in argumentation theory is of paramount importance. Recently, several argumentation based approaches have emerged to model uncertain data with probabilities. In this paper, we propose a new argumentation system called evidential argumentation framework that takes into account imprecision and uncertainty modeled by means of evidence theory. Indeed, evidence theory brings new semantics since arguments represent expert opinions with several weighted alternatives. Then, the evidential argumentation framework is studied in the light of both Smets and Demspter-Shafer interpretations of evidence theory. For each interpretation, we generalize Dung’s standard semantics with illustrative examples. We also investigate several preference criteria for pairwise comparison of extensions in order to select the ones that represent potential solutions to a given decision making problem.
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Notes
- 1.
A certain bba expresses the total certainty. It is defined as follows: \(m(A)=1\) and \(m(B)=0\) for all \(B \ne A\) and \(B\subseteq \varTheta \), where A is a singleton event of \(\varTheta \).
- 2.
Let \(x_1, x_2, x^{'}_1, x^{'}_2\) be four alternatives. Then \((x_1, x_2) \ge _{pareto} (x^{'}_1, x^{'}_2)\) iff \(\forall i \in [1, 2]\), \(x_i \ge x^{'}_i\) and \(\exists ~ j\), such that \(x_j > x^{'}_j\).
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Samet, A., Raddaoui, B., Dao, TT., Hadjali, A. (2016). Argumentation Framework Based on Evidence Theory. In: Carvalho, J., Lesot, MJ., Kaymak, U., Vieira, S., Bouchon-Meunier, B., Yager, R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2016. Communications in Computer and Information Science, vol 611. Springer, Cham. https://doi.org/10.1007/978-3-319-40581-0_21
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