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Harnessing Incremental Answer Set Solving for Reasoning in Assumption-Based Argumentation

Published online by Cambridge University Press:  22 November 2021

TUOMO LEHTONEN Open the ORCID record for TUOMO LEHTONEN [Opens in a new window] ,
JOHANNES P. WALLNER  and
MATTI JӒRVISALO
TUOMO LEHTONEN
Affiliation:
University of Helsinki, Helsinki, Finland (e-mail: tuomo.lehtonen@helsinki.fi)
JOHANNES P. WALLNER
Affiliation:
Graz University of Technology, Graz, Austria (e-mail: wallner@ist.tugraz.at)
MATTI JӒRVISALO
Affiliation:
University of Helsinki, Helsinki, Finland (e-mail: matti.jarvisalo@helsinki.fi)
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Abstract

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Assumption-based argumentation (ABA) is a central structured argumentation formalism. As shown recently, answer set programming (ASP) enables efficiently solving NP-hard reasoning tasks of ABA in practice, in particular in the commonly studied logic programming fragment of ABA. In this work, we harness recent advances in incremental ASP solving for developing effective algorithms for reasoning tasks in the logic programming fragment of ABA that are presumably hard for the second level of the polynomial hierarchy, including skeptical reasoning under preferred semantics as well as preferential reasoning. In particular, we develop non-trivial counterexample-guided abstraction refinement procedures based on incremental ASP solving for these tasks. We also show empirically that the procedures are significantly more effective than previously proposed algorithms for the tasks.

Keywords

answer set programmingincremental answer set solvingassumption-based argumentationstructured argumentationalgorithmsexperimental evaluation
Type
Original Article
Information
Theory and Practice of Logic Programming , Volume 21 , Special Issue 6: 37th International Conference on Logic Programming Special Issue II , November 2021 , pp. 717 - 734
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Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2021. Published by Cambridge University Press

Footnotes

*

Work financially supported by Academy of Finland (grant 322869), University of Helsinki Doctoral Programme in Computer Science DoCS, and the Austrian Science Fund (FWF): P30168-N31 and I2854.

References

Bao, Z., Čyras, K. and Toni, F. 2017. ABAplus: Attack reversal in abstract and structured argumentation with preferences. In Proc. PRIMA. LNCS, vol. 10621. Springer, 420–437.Google Scholar
Baroni, P., Gabbay, D., Giacomin, M. and van der Torre, L., Eds. 2018. Handbook of Formal Argumentation. College Publications.Google Scholar
Besnard, P. and Hunter, A. 2018. A review of argumentation based on deductive arguments. In Handbook of Formal Argumentation. College Publications, Chapter 9, 437–484.Google Scholar
Bondarenko, A., Dung, P. M., Kowalski, R. A. and Toni, F. 1997. An abstract, argumentation-theoretic approach to default reasoning. Artificial Intelligence 93, 63–101.10.1016/S0004-3702(97)00015-5CrossRefGoogle Scholar
Brewka, G., Delgrande, J. P., Romero, J. and Schaub, T. 2015. asprin: Customizing answer set preferences without a headache. In Proc. AAAI. AAAI Press, 1467–1474.Google Scholar
Caminada, M. and Schulz, C. 2017. On the equivalence between assumption-based argumentation and logic programming. Journal of Artificial Intelligence Research 60, 779–825.10.1613/jair.5581CrossRefGoogle Scholar
Cerutti, F., Gaggl, S. A., Thimm, M., and Wallner, J. P. 2018. Foundations of implementations for formal argumentation. In Handbook of Formal Argumentation. College Publications, Chapter 15, 688–767.Google Scholar
Clarke, E. M., Grumberg, O., Jha, S., Lu, Y. and Veith, H. 2003. Counterexample-guided abstraction refinement for symbolic model checking. Journal of the ACM 50, 5, 752–794.Google Scholar
Clarke, E. M., Gupta, A. and Strichman, O. 2004. SAT-based counterexample-guided abstraction refinement. IEEE Transactions on Computer Aided Design of Integrated Circuits and Systems 23, 7, 1113–1123.10.1109/TCAD.2004.829807CrossRefGoogle Scholar
Craven, R. and Toni, F. 2016. Argument graphs and assumption-based argumentation. Artificial Intelligence 233, 1–59.Google Scholar
Craven, R., Toni, F. and Williams, M. 2013. Graph-based dispute derivations in assumption-based argumentation. In TAFA 2013 Revised Selected Papers. LNCS, vol. 8306. Springer, 46–62.Google Scholar
Čyras, K. 2017. ABA+: Assumption-based argumentation with preferences. Ph.D. thesis, Imperial College London, UK.Google Scholar
Čyras, K., Fan, X., Schulz, C. and Toni, F. 2018. Assumption-based argumentation: Disputes, explanations, preferences. In Handbook of Formal Argumentation. College Publications, Chapter 7, 365–408.Google Scholar
Čyras, K. and Oliveira, T. 2019. Resolving conflicts in clinical guidelines using argumentation. In Proc. AAMAS. IFAAMAS, 1731–1739.Google Scholar
Čyras, K. and Toni, F. 2016a. ABA+: Assumption-based argumentation with preferences. In Proc. KR. AAAI Press, 553–556.Google Scholar
Čyras, K. and Toni, F. 2016b. Properties of ABA+ for non-monotonic reasoning. In Proc. NMR. 25–34.Google Scholar
Dimopoulos, Y., Nebel, B. and Toni, F. 2002. On the computational complexity of assumption-based argumentation for default reasoning. Artificial Intelligence 141, 1/2, 57–78.Google Scholar
Dung, P. M., Kowalski, R. A. and Toni, F. 2006. Dialectic proof procedures for assumption-based, admissible argumentation. Artificial Intelligence 170, 2, 114–159.10.1016/j.artint.2005.07.002CrossRefGoogle Scholar
Dung, P. M., Toni, F. and Mancarella, P. 2010. Some design guidelines for practical argumentation systems. In Proc. COMMA. FAIA, vol. 216. IOS Press, 183–194.Google Scholar
Fan, X. and Toni, F. 2016. On the interplay between games, argumentation and dialogues. In Proc. AAMAS. ACM, 260–268.Google Scholar
Fan, X., Toni, F., Mocanu, A. and Williams, M. 2014. Dialogical two-agent decision making with assumption-based argumentation. In Proc. AAMAS. IFAAMAS/ACM, 533–540.Google Scholar
Gaertner, D. and Toni, F. 2007. CaSAPI: A system for credulous and sceptical argumentation. In Proc. NMR. 80–95.Google Scholar
Garca, A. J. and Simari, G. R. 2018. Argumentation based on logic programming. In Handbook of Formal Argumentation. College Publications, Chapter 8, 409–435.Google Scholar
Gebser, M., Kaminski, R., Kaufmann, B., Ostrowski, M., Schaub, T. and Wanko, P. 2016. Theory solving made easy with Clingo 5. In Technical Communications of ICLP. OASICS. Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2:1–2:15.Google Scholar
Gebser, M., Kaufmann, B., Kaminski, R., Ostrowski, M., Schaub, T. and Schneider, M. T. 2011. Potassco: The Potsdam answer set solving collection. AI Communications 24, 2, 107–124.10.3233/AIC-2011-0491CrossRefGoogle Scholar
Gelfond, M. and Lifschitz, V. 1988. The stable model semantics for logic programming. In Proc. ICLP/SLP. MIT Press, 1070–1080.Google Scholar
Kaminski, R., Romero, J., Schaub, T. and Wanko, P. 2020. How to build your own ASP-based system?! CoRR abs/2008.06692.10.1017/S1471068421000508CrossRefGoogle Scholar
Lehtonen, T., Wallner, J. P. and Järvisalo, M. 2017. From structured to abstract argumentation: Assumption-based acceptance via AF reasoning. In Proc. ECSQARU. LNCS, vol. 10369. Springer, 57–68.Google Scholar
Lehtonen, T., Wallner, J. P. and Järvisalo, M. 2021a. Declarative algorithms and complexity results for assumption-based argumentation. Journal of Artificial Intelligence Research 71, 265–318.10.1613/jair.1.12479CrossRefGoogle Scholar
Lehtonen, T., Wallner, J. P. and Järvisalo, M. 2021b. Harnessing incremental answer set solving for reasoning in assumption-based argumentation. CoRR abs/2108.04192. Google Scholar
Modgil, S. and Prakken, H. 2018. Abstract rule-based argumentation. In Handbook of Formal Argumentation. College Publications, Chapter 6, 287–364.Google Scholar
Niemelä, I. 1999. Logic programs with stable model semantics as a constraint programming paradigm. Annals of Mathematics and Artificial Intelligence 25, 3–4, 241–273.10.1023/A:1018930122475CrossRefGoogle Scholar
Toni, F. 2013. A generalised framework for dispute derivations in assumption-based argumentation. Artificial Intelligence 195, 1–43.Google Scholar
Toni, F. 2014. A tutorial on assumption-based argumentation. Argument & Computation 5, 1, 89–117.10.1080/19462166.2013.869878CrossRefGoogle Scholar
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