Skip to main content
Log in

Probabilistic Argumentation: An Equational Approach

  • Published:
Logica Universalis Aims and scope Submit manuscript

Abstract

There is a generic way to add any new feature to a system. It involves (1) identifying the basic units which build up the system and (2) introducing the new feature to each of these basic units. In the case where the system is argumentation and the feature is probabilistic we have the following. The basic units are: (a) the nature of the arguments involved; (b) the membership relation in the set S of arguments; (c) the attack relation; and (d) the choice of extensions. Generically to add a new aspect (probabilistic, or fuzzy, or temporal, etc) to an argumentation network \({\langle S,R \rangle}\) can be done by adding this feature to each component (a–d). This is a brute-force method and may yield a non-intuitive or meaningful result. A better way is to meaningfully translate the object system into another target system which does have the aspect required and then let the target system endow the aspect on the initial system. In our case we translate argumentation into classical propositional logic and get probabilistic argumentation from the translation. Of course what we get depends on how we translate. In fact, in this paper we introduce probabilistic semantics to abstract argumentation theory based on the equational approach to argumentation networks. We then compare our semantics with existing proposals in the literature including the approaches by M. Thimm and by A. Hunter. Our methodology in general is discussed in the conclusion.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Caminada, M., Gabbay, D.: A logical account of formal argumentation. Studia Logica, 109–145 (2012)

  2. Caminada M., Pigozzi G.: On judgment aggregation in abstract argumentation. Auton. Agents Multi Agent Syst. 22(1), 64–102 (2011)

    Article  Google Scholar 

  3. Dung, P.M., Thang, P.: Towards (probabilistic) argumentation for jury-based depute resolution. In: Verheij, B., Szeider, S., Woltran, S. (eds.) Proceedings of COMMA III, Frontiers in Artificial Intelligence and Applications, pp. 171–182. IOS Press (2012)

  4. Gabbay, D.: Logics for Artificial Intelligence and Information Technology. College Publications, (2007)

  5. Gabbay, D.: Equational approach to argumentation networks. Argum. Comput. 87–142 (2012)

  6. Gabbay, D.M. Rodrigues, O.: A self-correcting iteration schema for argumentation networks. In: Parsons, S., Oren, N., Reed, C., Cerutti, F. (eds.) Proceedings of COMMA V, Frontiers in Artificial Intelligence and Applications, pp. 377 – 384. IOS Press (2014). doi:10.3233/978-1-61499-436-7-377

  7. Hunter, A.: Some foundations for probabilistic abstract argumentation. In: Verheij, B., Szeider, S., Woltran, S. (eds.) Proceedings of COMMA IV, Frontiers in Artificial Intelligence and Applications, pp. 117–128. IOS Press (2012)

  8. Hunter A.: A probabilistic approach to modelling uncertain logical arguments. Int. J. Approx. Reason. 54, 47–81 (2013)

    Article  MATH  Google Scholar 

  9. Li, H., Oren, N., Norman, T.: Probabilistic argumentation frameworks. In: Proceedings of the First International Workshop on the Theory and Applications of Formal Argumentation (TAFA’11), vol. 7132 of Lecture Notes in Computer Science. Springer, (2012)

  10. Modgil S., Prakken H.: the ASPIC+ framework for structured argumentation: A tutorial. Argum. Comput. 5(1), 31–62 (2014)

    Article  Google Scholar 

  11. Paris, J.B.: The Uncertain Reasoner’s Companion. A Mathematical Perspective. Cambridge University Press (2006)

  12. Pearl, J.: Probabilistic Reasoning in Intelligent Systems. Networks of Plausible Inference. Morgan Kaufmann (1998)

  13. Thimm, M.: A probabilistic semantics for abstract argumentation. In: Proceedings of the 20th European Conference on Artificial Intelligence (ECAI’12) (2012)

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to O. Rodrigues.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gabbay, D.M., Rodrigues, O. Probabilistic Argumentation: An Equational Approach. Log. Univers. 9, 345–382 (2015). https://doi.org/10.1007/s11787-015-0120-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11787-015-0120-1

Mathematics Subject Classification

Keywords

Navigation