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Preservation of Admissibility with Rationality and Feasibility Constraints

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Logic and Argumentation (CLAR 2020)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12061))

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Abstract

The paper considers the problem of in what circumstances an aggregation rule guarantees an admissible output extension that represents a good compromise between several input extensions of abstract argumentation framework, each provided by a different individual. To achieve this, we introduce the concept of concrete admissibility for abstract argumentations by strengthening Dung’s admissibility. We also define a model for extension aggregation that clearly separates the constraint supposed to be satisfied by individuals and the constraint that must be met by the collective decision. Using this model, we show that the majority rule guarantees admissible sets on newly defined admissible sets.

Supported by the MOE Project of Key Research Institute of Humanities and Social Sciences in Universities, No. 18JJD720005, the China Postdoctoral Science Foundation Grant, No. 2019M663352, and the Philosophy and Social Science Youth Projects of Guangdong Province, No. GD19CZX03.

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References

  1. Awad, E., Booth, R., Tohmé, F., Rahwan, I.: Judgement aggregation in multi-agent argumentation. J. Logic Comput. 27(1), 227–259 (2017)

    Article  MathSciNet  Google Scholar 

  2. Baroni, P., Caminada, M., Giacomin, M.: An introduction to argumentation semantics. Knowl. Eng. Rev. 26(4), 365–410 (2011)

    Article  Google Scholar 

  3. Besnard, P., Doutre, S.: Checking the acceptability of a set of arguments. In: Proceedings of the 10th International Workshop on Non-Monotonic Reasoning (NMR) (2004)

    Google Scholar 

  4. Booth, R., Awad, E., Rahwan, I.: Interval methods for judgment aggregation in argumentation. In: Proceedings of the 14th International Conference on Principles of Knowledge Representation and Reasoning (KR) (2014)

    Google Scholar 

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

    Article  Google Scholar 

  6. Chen, W., Endriss, U.: Aggregating alternative extensions of abstract argumentation frameworks: preservation results for quota rules. In: Proceedings of the 7th International Conference on Computational Models of Argument (COMMA). IOS Press (2018)

    Google Scholar 

  7. Dietrich, F., List, C.: Judgment aggregation by quota rules: majority voting generalized. J. Theor. Politics 19(4), 391–424 (2007)

    Article  Google Scholar 

  8. Dung, P.M.: 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  Google Scholar 

  9. Endriss, U.: Judgment aggregation. In: Brandt, F., Conitzer, V., Endriss, U., Lang, J., Procaccia, A.D. (eds.) Handbook of Computational Social Choice, pp. 399–426. Cambridge University Press, Cambridge (2016). Chap. 17

    Chapter  Google Scholar 

  10. Endriss, U.: Judgment aggregation with rationality and feasibility constraints. In: Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2018), July 2018

    Google Scholar 

  11. Endriss, U., Grandi, U., Porello, D.: Complexity of judgment aggregation. J. Artif. Intell. Res. (JAIR) 45, 481–514 (2012)

    Article  MathSciNet  Google Scholar 

  12. Grandi, U., Endriss, U.: Lifting integrity constraints in binary aggregation. Artif. Intell. 199–200, 45–66 (2013)

    Article  MathSciNet  Google Scholar 

  13. Grossi, D., Modgil, S.: On the graded acceptability of arguments in abstract and instantiated argumentation. Artif. Intell. 275, 138–173 (2019)

    Article  MathSciNet  Google Scholar 

  14. Grossi, D., Pigozzi, G.: Judgment Aggregation: A Primer. Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan & Claypool Publishers, San Rafael (2014)

    Google Scholar 

  15. List, C., Pettit, P.: Aggregating sets of judgments: an impossibility result. Econ. Philos. 18(1), 89–110 (2002)

    Article  Google Scholar 

  16. Marquis, P.: Consequence finding algorithms. In: Kohlas, J., Moral, S. (eds.) Handbook of Defeasible Reasoning and Uncertainty Management Systems, vol. 5, pp. 41–145. Springer, Dordrecht (2000). https://doi.org/10.1007/978-94-017-1737-3_3

    Chapter  Google Scholar 

  17. Rahwan, I., Tohmé, F.A.: Collective argument evaluation as judgement aggregation. In: Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), IFAAMAS (2010)

    Google Scholar 

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Correspondence to Weiwei Chen .

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Chen, W. (2020). Preservation of Admissibility with Rationality and Feasibility Constraints. In: Dastani, M., Dong, H., van der Torre, L. (eds) Logic and Argumentation. CLAR 2020. Lecture Notes in Computer Science(), vol 12061. Springer, Cham. https://doi.org/10.1007/978-3-030-44638-3_15

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  • DOI: https://doi.org/10.1007/978-3-030-44638-3_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-44637-6

  • Online ISBN: 978-3-030-44638-3

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