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A Parametrized Ranking-Based Semantics for Persuasion

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Scalable Uncertainty Management (SUM 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10564))

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Abstract

In this paper we question the ability of the existant ranking semantics for argumentation to capture persuasion settings, emphasizing in particular the phenomena of protocatalepsis (the fact that it is often efficient to anticipate the counter-arguments of the audience), and of fading (the fact that long lines of argumentation become ineffective). It turns out that some widely accepted principles of ranking-based semantics are incompatible with a faithful treatment of these phenomena. We thus propose a parametrized semantics based on propagation of values, which allows to control the scope of arguments to be considered for evaluation. We investigate its properties (identifying in particular threshold values guaranteeing that some properties hold), and report experimental results showing that the family of rankings that may be returned have a high coherence rate.

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Notes

  1. 1.

    The generation algorithms are based on the three algorithms used for producing the benchmarks of the competition ICCMA’15 (see http://argumentationcompetition.org/2015/results.html).

References

  1. Amgoud, L., Ben-Naim, J.: Ranking-based semantics for argumentation frameworks. In: Liu, W., Subrahmanian, V.S., Wijsen, J. (eds.) SUM 2013. LNCS, vol. 8078, pp. 134–147. Springer, Heidelberg (2013). doi:10.1007/978-3-642-40381-1_11

    Chapter  Google Scholar 

  2. Amgoud, L., Ben-Naim, J., Doder, D., Vesic, S.: Ranking arguments with compensation-based semantics. In: Proceedings of the 15th International Conference on Principles of Knowledge Representation and Reasoning (KR 2016), pp. 12–21 (2016)

    Google Scholar 

  3. Besnard, P., Hunter, A.: A logic-based theory of deductive arguments. Artif. Intell. 128(1–2), 203–235 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  4. Besnard, P., Hunter, A.: Elements of Argumentation. MIT Press (2008)

    Google Scholar 

  5. Bonzon, E., Delobelle, J., Konieczny, S., Maudet, N.: A comparative study of ranking-based semantics for abstract argumentation. In: Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI 2016), pp. 914–920 (2016)

    Google Scholar 

  6. Bonzon, E., Delobelle, J., Konieczny, S., Maudet, N.: Argumentation ranking semantics based on propagation. In: Proceedings of the 6th International Conference on Computational Models of Argument (COMMA 2016), pp. 139–150 (2016)

    Google Scholar 

  7. Cayrol, C., Lagasquie-Schiex, M.-C.: Graduality in argumentation. J. Artif. Intell. Res. 23, 245–297 (2005)

    MathSciNet  MATH  Google Scholar 

  8. Correia, M., Cruz, J., Leite, J.: On the efficient implementation of social abstract argumentation. In: Proceedings of the 21st European Conference on Artificial Intelligence (eCAI 2014), pp. 225–230 (2014)

    Google Scholar 

  9. da Costa Pereira, C., Tettamanzi, A., Villata, S.: Changing one’s mind: erase or rewind? In: Proceedings of the 22nd International Joint Conference on Artificial Intelligence, (IJCAI 2011), pp. 164–171 (2011)

    Google Scholar 

  10. Dung, P.H.: On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artif. Intell. 77(2), 321–358 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  11. Eğilmez, S., Martins, J., Leite, J.: Extending social abstract argumentation with votes on attacks. In: Black, E., Modgil, S., Oren, N. (eds.) TAFA 2013. LNCS, vol. 8306, pp. 16–31. Springer, Heidelberg (2014). doi:10.1007/978-3-642-54373-9_2

    Chapter  Google Scholar 

  12. Gabbay, D.M.: Equational approach to argumentation networks. Argument Comput. 3(2–3), 87–142 (2012)

    Article  Google Scholar 

  13. Grossi, D., Modgil, S.: On the graded acceptability of arguments. In: Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI 2015), pp. 868–874 (2015)

    Google Scholar 

  14. Hunter, A.: Opportunities for argument-centric persuasion in behaviour change. In: Fermé, E., Leite, J. (eds.) JELIA 2014. LNCS, vol. 8761, pp. 48–61. Springer, Cham (2014). doi:10.1007/978-3-319-11558-0_4

    Google Scholar 

  15. Kendall, M.G.: A new measure of rank correlation. Biometrika 30(1/2), 81–93 (1938)

    Article  MATH  Google Scholar 

  16. Leite, J., Martins, J.: Social abstract argumentation. In: Proceedings of the 22nd International Joint Conference on Artificial Intelligence, (IJCAI 2011), pp. 2287–2292 (2011)

    Google Scholar 

  17. Matt, P.-A., Toni, F.: A game-theoretic measure of argument strength for abstract argumentation. In: Hölldobler, S., Lutz, C., Wansing, H. (eds.) JELIA 2008. LNCS, vol. 5293, pp. 285–297. Springer, Heidelberg (2008). doi:10.1007/978-3-540-87803-2_24

    Chapter  Google Scholar 

  18. Pu, F., Luo, J., Luo, G.: Some supplementaries to the counting semantics for abstract argumentation. In: Proceedings of the 27th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2015), pp. 242–249 (2015)

    Google Scholar 

  19. Pu, F., Luo, J., Zhang, Y., Luo, G.: Argument ranking with categoriser function. In: Buchmann, R., Kifor, C.V., Yu, J. (eds.) KSEM 2014. LNCS, vol. 8793, pp. 290–301. Springer, Cham (2014). doi:10.1007/978-3-319-12096-6_26

    Google Scholar 

  20. Pu, F., Luo, J., Zhang, Y., Luo, G.: Attacker and defender counting approach for abstract argumentation. In: Proceedings of the 37th Annual Meeting of the Cognitive Science Society (CogSci 2015) (2015)

    Google Scholar 

  21. Tan, C., Niculae, V., Danescu-Niculescu-Mizil, C., Lee, L.: Winning arguments: interaction dynamics and persuasion strategies in good-faith online discussions. In: Proceedings of the 25th International Conference on World Wide Web (WWW 2016), pp. 613–624 (2016)

    Google Scholar 

  22. Walton, D.: Dialog Theory for Critical Argumentation. John Benjamins Publishing (2007)

    Google Scholar 

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Acknowledgements

This work benefited from the support of the project AMANDE ANR-13-BS02-0004 of the French National Research Agency (ANR).

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Correspondence to Jérôme Delobelle .

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Bonzon, E., Delobelle, J., Konieczny, S., Maudet, N. (2017). A Parametrized Ranking-Based Semantics for Persuasion. In: Moral, S., Pivert, O., Sánchez, D., Marín, N. (eds) Scalable Uncertainty Management. SUM 2017. Lecture Notes in Computer Science(), vol 10564. Springer, Cham. https://doi.org/10.1007/978-3-319-67582-4_17

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  • DOI: https://doi.org/10.1007/978-3-319-67582-4_17

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