research-article

Abstract argumentation framework with conditional preferences

AUTHORs:

Gianvincenzo Alfano,

Francesco Parisi,

Irina TrubitsynaAuthors Info & Claims

AAAI'23/IAAI'23/EAAI'23: Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence and Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence and Thirteenth Symposium on Educational Advances in Artificial Intelligence

Article No.: 697, Pages 6218 - 6227

https://doi.org/10.1609/aaai.v37i5.25766

Published: 07 February 2023 Publication History

Abstract

Dung's abstract Argumentation Framework (AF) has emerged as a central formalism in the area of knowledge representation and reasoning. Preferences in AF allow to represent the comparative strength of arguments in a simple yet expressive way. Preference-based AF (PAF) has been proposed to extend AF with preferences of the form a > b, whose intuitive meaning is that argument a is better than b. In this paper we generalize PAF by introducing conditional preferences of the form a > b ⅲ body that informally state that a is better than b whenever the condition expressed by body is true. The resulting framework, namely Conditional Preference-based AF (CPAF), extends the PAF semantics under three well-known preference criteria, i.e. democratic, elitist, and KTV. After introducing CPAF, we study the complexity of the verification problem (deciding whether a set of arguments is a "best" extension) as well as of the credulous and skeptical acceptance problems (deciding whether a given argument belongs to any or all "best" extensions, respectively) under multiple-status semantics (that is, complete, preferred, stable, and semi-stable semantics) for the above-mentioned preference criteria.

References

[1]

Alfano, G.; Calautti, M.; Greco, S.; Parisi, F.; and Trubitsyna, I. 2020a. Explainable Acceptance in Probabilistic Abstract Argumentation: Complexity and Approximation. In Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning, 33-43.

[2]

Alfano, G.; Cohen, A.; Gottifredi, S.; Greco, S.; Parisi, F.; and Simari, G. 2020b. Dynamics in Abstract Argumentation Frameworks with Recursive Attack and Support Relations. In Proceedings of the 24th European Conference on Artificial Intelligence (ECAI), 577-584.

[3]

Alfano, G.; and Greco, S. 2021. Incremental Skeptical Preferred Acceptance in Dynamic Argumentation Frameworks. IEEE Intell. Syst., 36(2): 6-12.

[4]

Alfano, G.; Greco, S.; and Parisi, F. 2018. A meta-argumentation approach for the efficient computation of stable and preferred extensions in dynamic bipolar argumentation frameworks. Intelligenza Artificiale, 12(2): 193-211.

[5]

Alfano, G.; Greco, S.; and Parisi, F. 2021. Incremental Computation in Dynamic Argumentation Frameworks. IEEE Intell. Syst., 36(6): 80-86.

Digital Library

[6]

Alfano, G.; Greco, S.; Parisi, F.; Simari, G. I.; and Simari, G. R. 2018. An Incremental Approach to Structured Argumentation over Dynamic Knowledge Bases. In Proceedings of International Conference on Principles of Knowledge Representation and Reasoning (KR), 78-87.

[7]

Alfano, G.; Greco, S.; Parisi, F.; Simari, G. I.; and Simari, G. R. 2021a. Incremental computation for structured argumentation over dynamic DeLP knowledge bases. Artif. Intell., 300: 103553.

Digital Library

[8]

Alfano, G.; Greco, S.; Parisi, F.; and Trubitsyna, I. 2020c. On the Semantics of Abstract Argumentation Frameworks: A Logic Programming Approach. Theory Pract. Log. Program., 20(5): 703-718.

[9]

Alfano, G.; Greco, S.; Parisi, F.; and Trubitsyna, I. 2021b. Argumentation Frameworks with Strong and Weak Constraints: Semantics and Complexity. In Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 6175-6184.

[10]

Alfano, G.; Greco, S.; Parisi, F.; and Trubitsyna, I. 2022a. Incomplete Argumentation Frameworks: Properties and Complexity. In Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 5451-5460.

[11]

Alfano, G.; Greco, S.; Parisi, F.; and Trubitsyna, I. 2022b. On Preferences and Priority Rules in Abstract Argumentation. In Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2517-2524.

[12]

Alfano, G.; Greco, S.; Parisi, F.; and Trubitsyna, I. 2023. On acceptance conditions in abstract argumentation frameworks. Information Sciences, 625: 757-779.

Digital Library

[13]

Allen, T. E.; Goldsmith, J.; Justice, H. E.; Mattei, N.; and Raines, K. 2017. Uniform Random Generation and Dominance Testing for CP-Nets. J. Artif. Intell. Res., 59: 771-813.

Digital Library

[14]

Amgoud, L.; and Cayrol, C. 1998. On the Acceptability of Arguments in Preference-based Argumentation. In Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, 17.

[15]

Amgoud, L.; and Cayrol, C. 2002. Inferring from Inconsistency in Preference-Based Argumentation Frameworks. J. Autom. Reason., 29(2): 125-169.

Digital Library

[16]

Amgoud, L.; and Vesic, S. 2011. A new approach for preference-based argumentation frameworks. Ann. Math. Artif. Intell., 63(2): 149-183.

Digital Library

[17]

Amgoud, L.; and Vesic, S. 2014. Rich preference-based argumentation frameworks. Int. J. Approx. Reason., 55(2): 585-606.

Digital Library

[18]

Baumann, R.; and Brewka, G. 2019. Extension Removal in Abstract Argumentation - An Axiomatic Approach. In Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2670-2677.

[19]

Bench-Capon, T. J. M. 2003. Persuasion in Practical Argument Using Value-based Argumentation Frameworks. J. Log. Comput., 13(3): 429-448.

[20]

Bernreiter, M.; Dvor�k, W.; and Woltran, S. 2022. Abstract Argumentation with Conditional Preferences. In Proc. of COMMA, 92-103.

[21]

Bonzon, E.; Delobelle, J.; Konieczny, S.; and Maudet, N. 2016. A Comparative Study of Ranking-Based Semantics for Abstract Argumentation. In Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 914-920.

[22]

Boutilier, C.; Brafman, R. I.; Domshlak, C.; Hoos, H. H.; and Poole, D. 2004. CP-nets: A Tool for Representing and Reasoning with Conditional Ceteris Paribus Preference Statements. J. Artif. Intell. Res., 21: 135-191.

[23]

Brafman, R. I.; and Domshlak, C. 2009. Preference Handling - An Introductory Tutorial. AI Mag., 30(1): 58-86.

Digital Library

[24]

Brarda, M. E. B.; Tamargo, L. H.; and Garcia, A. J. 2019. An approach to enhance argument-based multi-criteria decision systems with conditional preferences and explainable answers. Expert Syst. Appl., 126: 171-186.

Digital Library

[25]

Brewka, G. 1989. Preferred Subtheories: An Extended Logical Framework for Default Reasoning. In Proceedings of the 11th International Joint Conference on Artificial Intelligence, 1043-1048.

[26]

Brewka, G.; Delgrande, J. P.; Romero, J.; and Schaub, T. 2015. asprin: Customizing Answer Set Preferences without a Headache. In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 1467-1474.

[27]

Brewka, G.; and Eiter, T. 1999. Preferred Answer Sets for Extended Logic Programs. Artif. Intell., 109(1-2): 297-356.

Digital Library

[28]

Brewka, G.; Niemel�, I.; and Truszczynski, M. 2003. Answer Set Optimization. In Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, 867-872.

[29]

Cayrol, C.; Cohen, A.; and Lagasquie-Schiex, M. 2021. HigherOrder Interactions (Bipolar or not) in Abstract Argumentation: A State of the Art. In Handbook of Formal Argumentation, volume 2, chapter 1. College Publications.

[30]

Coste-Marquis, S.; Konieczny, S.; Marquis, P.; and Ouali, M. A. 2012. Weighted Attacks in Argumentation Frameworks. In Proceedings of the Thirteenth International Conference on Principles of Knowledge Representation and Reasoning.

[31]

Cyras, K. 2016. Argumentation-Based Reasoning with Preferences. In Highlights of Practical Applications of Scalable MultiAgent Systems. The PAAMS Collection - International Workshops of PAAMS, 199-210.

[32]

Cyras, K.; Fan, X.; Schulz, C.; and Toni, F. 2018. Assumption-based Argumentation: Disputes, Explanations, Preferences. In Handbook of Formal Argumentation, volume 1, chapter 7. College Publications.

[33]

Delgrande, J. P.; Schaub, T.; and Tompits, H. 2003. A Framework for Compiling Preferences in Logic Programs. Theory Pract. Log. Program., 3(2): 129-187.

Digital Library

[34]

Dung, P. M. 1995. On the Acceptability of Arguments and its Fundamental Role in Nonmonotonic Reasoning, Logic Programming and n-Person Games. Artif. Intell., 77: 321-358.

Digital Library

[35]

Dung, P. M.; Thang, P. M.; and Son, T. C. 2019. On Structured Argumentation with Conditional Preferences. In Proceeding of the Thirty-Third AAAI Conference on Artificial Intelligence, 2792-2800.

[36]

Dunne, P. E.; and Bench-Capon, T. J. M. 2004. Complexity in Value-Based Argument Systems. In Proceedings of the 14th European Conference on Logics in Artificial Intelligence, 360-371.

[37]

Dunne, P. E.; Hunter, A.; McBurney, P.; Parsons, S.; and Wooldridge, M. J. 2011. Weighted argument systems: Basic definitions, algorithms, and complexity results. Artif. Intell., 175(2): 457-486.

Digital Library

[38]

Dvorak, W.; and Dunne, P. E. 2018. Computational Problems in Formal Argumentation and their Complexity. In Handbook of Formal Argumentation, volume 1, chapter 13. College Publications.

[39]

Eiter, T.; Faber, W.; Leone, N.; and Pfeifer, G. 2003. Computing preferred answer sets by meta-interpretation in answer set programming. Theory Pract. Log. Program., 3(4-5): 463-498.

Digital Library

[40]

Fazzinga, B.; Flesca, S.; and Furfaro, F. 2020. Revisiting the Notion of Extension over Incomplete Abstract Argumentation Frameworks. In Proc. of IJCAI, 1712-1718.

[41]

Fazzinga, B.; Flesca, S.; and Parisi, F. 2015. On the Complexity of Probabilistic Abstract Argumentation Frameworks. ACM Trans. Comput. Log., 16(3): 22:1-22:39.

Digital Library

[42]

Fishburn, P. C. 1972. Even-chance lotteries in social choice theory. Theory and Decision, 3(1): 18-40.

[43]

Gabbay, D.; Giacomin, M.; Simari, G. R.; and Thimm, M., eds. 2021. Handbook of Formal Argumentation, volume 2. College Publications.

[44]

Ganzer-Ripoll, J.; Criado, N.; Lopez-Sanchez, M.; Parsons, S.; and Rodriguez-Aguilar, J. A. 2019. Combining social choice theory and argumentation: Enabling collective decision making. Group Decision and Negotiation, 28(1): 127-173.

[45]

Garcia, A. J.; Prakken, H.; and Simari, G. R. 2020. A Comparative Study of Some Central Notions of ASPIC+ and DeLP. Theory Pract. Log. Program., 20(3): 358-390.

[46]

G�rdenfors, P. 1979. On definitions of manipulation of social choice functions. Aggregation and Revelation of Preferences. North-Holland, 78.

[47]

Goldsmith, J.; Lang, J.; Truszczynski, M.; and Wilson, N. 2008. The Computational Complexity of Dominance and Consistency in CP-Nets. J. Artif. Intell. Res., 33: 403-432.

[48]

Gottifredi, S.; Cohen, A.; Garcia, A. J.; and Simari, G. R. 2018. Characterizing acceptability semantics of argumentation frameworks with recursive attack and support relations. Artif. Intell., 262: 336-368.

Digital Library

[49]

Greco, S.; Trubitsyna, I.; and Zumpano, E. 2007. On the Semantics of Logic Programs with Preferences. J. Artif. Intell. Res., 30: 501-523.

[50]

Heyninck, J.; and Strasser, C. 2021. A Comparative Study of Assumption-based Argumentative Approaches to Reasoning with Priorities. Journal of Applied Logics - IfCoLog Journal, 8(3): 737-808.

[51]

Kaci, S.; van der Torre, L. W. N.; Vesic, S.; and Villata, S. 2021. Preference in Abstract Argumentation. In Handbook of Formal Argumentation, volume 2, chapter 3. College Publications.

[52]

Kelly, J. S. 1977. Strategy-proofness and social choice functions without singlevaluedness. Econometrica: Journal of the Econometric Society, 439-446.

[53]

Lukasiewicz, T.; and Malizia, E. 2019. Complexity results for preference aggregation over (m)CP-nets: Pareto and majority voting. Artif Intell., 272: 101-142.

Digital Library

[54]

Lukasiewicz, T.; and Malizia, E. 2022. Complexity results for preference aggregation over (m)CP-nets: Max and rank voting. Artif. Intell., 303: 103636.

Digital Library

[55]

Mailly, J.; and Rossit, J. 2020. Argument, I Choose You! Preferences and Ranking Semantics in Abstract Argumentation. In Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning, 647-651.

[56]

Modgil, S. 2009. Reasoning about preferences in argumentation frameworks. Artif Intell., 173(9-10): 901-934.

Digital Library

[57]

Modgil, S.; and Prakken, H. 2013. A general account of argumentation with preferences. Artif. Intell., 195: 361-397.

Digital Library

[58]

Modgil, S.; and Prakken, H. 2014. The ASPIC⁺ framework for structured argumentation: a tutorial. Argument Comput., 5(1): 31-62.

[59]

Niskanen, A.; and Jarvisalo, M. 2020. Algorithms for Dynamic Argumentation Frameworks: An Incremental SAT-Based Approach. In Proceedings of the 24th European Conference on Artificial Intelligence (ECAI), 849-856.

[60]

Papadimitriou, C. H. 1994. Computational complexity. Addison-Wesley.

[61]

Prakken, H. 2010. An abstract framework for argumentation with structured arguments. Argument & Computation, 1(2): 93-124.

[62]

Prakken, H.; and Sartor, G. 1997. Argument-Based Extended Logic Programming with Defeasible Priorities. J. Appl. Non Class. Logics, 7(1): 25-75.

[63]

Rossi, F.; Venable, K. B.; and Walsh, T. 2004. mCP Nets: Representing and Reasoning with Preferences of Multiple Agents. In Proceedings of the Nineteenth AAAI Conference on Artificial Intelligence, 729-734.

[64]

Sakama, C.; and Inoue, K. 2000. Prioritized logic programming and its application to commonsense reasoning. Artif. Intell., 123(1-2).

[65]

Sakama, C.; and Son, T. C. 2020. Epistemic Argumentation Framework: Theory and Computation. J. Artif. Intell. Res., 69: 1103-1126.

[66]

Schaub, T.; and Wang, K. 2001. A Comparative Study of Logic Programs with Preference. In Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, 597-602.

[67]

Silva, R.; S�, S.; and Alc�ntara, J. F. L. 2020. Semantics Hierarchy in Preference-Based Argumentation Frameworks. In Proceedings of the 8th International Conference on Computational Models of Argument, 339-346.

[68]

Teze, J. C.; Gottifredi, S.; Garc�a, A. J.; and Simari, G. R. 2020. An approach to generalizing the handling of preferences in argumentation-based decision-making systems. Knowl. Based Syst., 189.

[69]

Villata, S.; Boella, G.; Gabbay, D. M.; and van der Torre, L. W. N. 2012. Modelling defeasible and prioritized support in bipolar argumentation. Ann. Math. Artif. Intell., 66(1-4).

[70]

Wakaki, T. 2015. Preference-based argumentation built from prioritized logic programming. J. Log. Comput., 25(2): 251-301.

Cited By

Alfano GGreco SParisi FTrubitsyna IDastani MSichman JAlechina NDignum V(2024)On General Epistemic Abstract Argumentation FrameworksProceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems10.5555/3635637.3663079(2117-2119)Online publication date: 6-May-2024
https://dl.acm.org/doi/10.5555/3635637.3663079
Alfano GGreco SParisi FTrubitsyna IAgmon NAn BRicci AYeoh W(2023)Epistemic Abstract Argumentation Framework: Formal Foundations, Computation and ComplexityProceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems10.5555/3545946.3598664(409-417)Online publication date: 30-May-2023
https://dl.acm.org/doi/10.5555/3545946.3598664

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AAAI'23/IAAI'23/EAAI'23: Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence and Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence and Thirteenth Symposium on Educational Advances in Artificial Intelligence

February 2023

16496 pages

ISBN:978-1-57735-880-0

Copyright � 2023 Association for the Advancement of Artificial Intelligence.

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Published: 07 February 2023

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Cited By

Alfano GGreco SParisi FTrubitsyna IDastani MSichman JAlechina NDignum V(2024)On General Epistemic Abstract Argumentation FrameworksProceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems10.5555/3635637.3663079(2117-2119)Online publication date: 6-May-2024
https://dl.acm.org/doi/10.5555/3635637.3663079
Alfano GGreco SParisi FTrubitsyna IAgmon NAn BRicci AYeoh W(2023)Epistemic Abstract Argumentation Framework: Formal Foundations, Computation and ComplexityProceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems10.5555/3545946.3598664(409-417)Online publication date: 30-May-2023
https://dl.acm.org/doi/10.5555/3545946.3598664

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