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Stable Semantics in Logic-Based Argumentation

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 7520)

Abstract

This paper investigates the outputs of abstract logic-based argumentation systems under stable semantics. We delimit the number of stable extensions a system may have. We show that in the best case, an argumentation system infers exactly the common conclusions drawn from the maximal consistent subbases of the original knowledge base. This output corresponds to that returned by a system under the naive semantics. In the worst case, counter-intuitive results are returned. In the intermediary case, the system forgets intuitive conclusions. These two latter cases are due to the use of skewed attack relations. The results show that stable semantics is either useless or unsuitable in logic-based argumentation systems. Finally, we show that under this semantics, argumentation systems may inherit the problems of coherence-based approaches.

Keywords

  • Knowledge Base
  • Propositional Logic
  • Argumentation System
  • Attack Relation
  • Stable Extension

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Amgoud, L. (2012). Stable Semantics in Logic-Based Argumentation. In: Hüllermeier, E., Link, S., Fober, T., Seeger, B. (eds) Scalable Uncertainty Management. SUM 2012. Lecture Notes in Computer Science(), vol 7520. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33362-0_5

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  • DOI: https://doi.org/10.1007/978-3-642-33362-0_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33361-3

  • Online ISBN: 978-3-642-33362-0

  • eBook Packages: Computer ScienceComputer Science (R0)