article

SCC-recursiveness: a general schema for argumentation semantics

Authors:

Massimiliano Giacomin,

Giovanni GuidaAuthors Info & Claims

Artificial Intelligence, Volume 168, Issue 1-2

Pages 162 - 210

Published: 01 October 2005 Publication History

Abstract

In argumentation theory, Dung's abstract framework provides a unifying view of several alternative semantics based on the notion of extension. In this context, we propose a general recursive schema for argumentation semantics, based on decomposition along the strongly connected components of the argumentation framework. We introduce the fundamental notion of SCC-recursiveness and we show that all Dung's admissibility-based semantics are SCC-recursive, and therefore a special case of our schema. On these grounds, we argue that the concept of SCC-recursiveness plays a fundamental role in the study and definition of argumentation semantics. In particular, the space of SCC-recursive semantics provides an ideal basis for the investigation of new proposals: starting from the analysis of several examples where Dung's preferred semantics gives rise to questionable results, we introduce four novel SCC-recursive semantics, able to overcome the limitations of preferred semantics, while differing in other respects.

References

[1]

Amgoud, L. and Cayrol, C., Inferring from inconsistency in preference-based argumentation frameworks. J. Automat. Reason. v29 i2. 125-169.

[2]

Amgoud, L. and Cayrol, C., A reasoning model based on the production of acceptable arguments. Ann. Math. Artificial Intelligence. v34 i1--3. 197-215.

[3]

Amgoud, L., Parsons, S. and Maudet, N., Arguments, dialogue, and negotiation. In: Proceedings of the 14th European Conference on Artificial Intelligence (ECAI 2000), IOS Press, Berlin. pp. 338-342.

Digital Library

[4]

Baroni, P. and Giacomin, M., Solving semantic problems with odd-length cycles in argumentation. In: Lecture Notes in Artificial Intelligence, vol. 2711. Springer, Aalborg, Denmark. pp. 440-451.

[5]

P. Baroni, M. Giacomin, A recursive approach to argumentation: motivation and perspectives, in: Proceedings of the 10th International Workshop on Non-Monotonic Reasoning (NMR 2004), Whistler, BC, Canada, 2004, pp. 50--58

[6]

Baroni, P., Giacomin, M. and Guida, G., Extending abstract argumentation systems theory. Artificial Intelligence. v120 i2. 251-270.

[7]

P. Baroni, M. Giacomin, G. Guida, On the notion of strength in argumentation: overcoming the epistemic/practical dichotomy, in: Proceedings of the 2001 ECSQARU Workshop---Adventures in Argumentation Toulouse, France, 2001, pp. 1--8

[8]

P. Baroni, M. Giacomin, G. Guida, Towards a formalization of skepticism in extension-based argumentation semantics, in: Proceedings of the 4th Workshop on Computational Models of Natural Argument (CMNA 2004), Valencia, Spain, 2004, pp. 47--52

[9]

Dung, P.M., On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming, and n-person games. Artificial Intelligence. v77 i2. 321-357.

[10]

Garcia, A.J. and Simari, G.R., Defeasible logic programming: An argumentative approach. Theory Pract. Logic Programming. v4 i1. 95-138.

[11]

Horty, J.F., Skepticism and floating conclusions. Artificial Intelligence. v135 i1--2. 55-72.

[12]

Floating conclusions and zombie paths: Two deep difficulties in the 'directly skeptical' approach to defeasible inheritance networks. Artificial Intelligence. v48 i2. 199-209.

[13]

Pollock, J.L., How to reason defeasibly. Artificial Intelligence. v57 i1. 1-42.

[14]

Pollock, J.L., Justification and defeat. Artificial Intelligence. v67. 377-407.

[15]

Pollock, J.L., Cognitive Carpentry: A Blueprint for How to Build a Person. 1995. MIT Press, Cambridge, MA.

[16]

Pollock, J.L., The logical foundations of goal-regression planning in autonomous agents. Artificial Intelligence. v106 i2. 267-334.

[17]

Pollock, J.L., Perceiving and reasoning about a changing world. Comput. Intelligence. v14 i4. 498-562.

[18]

Pollock, J.L., Defeasible reasoning with variable degrees of justification. Artificial Intelligence. v133 i1--2. 233-282.

[19]

Prakken, H., Logical Tools for Modeling Legal Argument: A Study of Defeasible Reasoning in Law. 1997. Kluwer Academic, Dordrecht.

[20]

H. Prakken, Intuitions and the modelling of defeasible reasoning: Some case studies, in: Proceedings of the 9th International Workshop on Non-Monotonic Reasoning (NMR 2002), Toulouse, France, 2002, pp. 91--102

[21]

Prakken, H. and Sartor, G., Argument-based extended logic programming with defeasible priorities. J. Appl. Non-Class. Logics. v7. 25-75.

[22]

Prakken, H. and Vreeswijk, G.A.W., Logics for defeasible argumentation. In: Gabbay, D.M., Guenthner, F. (Eds.), Handbook of Philosophical Logic, Kluwer Academic, Dordrecht.

[23]

Reiter, R., A logic for default reasoning. Artificial Intelligence. v13 i1--2. 81-132.

[24]

Schlechta, K., Directly sceptical inheritance cannot capture the intersection of extensions. J. Logic Comput. v3 i5. 455-467.

[25]

Simari, G.R. and Loui, R.P., A mathematical treatment of defeasible reasoning and its implementation. Artificial Intelligence. v53 i2--3. 125-157.

[26]

Verheij, B., Artificial argument assistants for defeasible argumentation. Artificial Intelligence. v150 i1--2. 291-324.

[27]

Vreeswijk, G.A.W., Abstract argumentation systems. Artificial Intelligence. v90 i1--2. 225-279.

Cited By

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
Bl�mel LThimm MMarquis PSon TKern-Isberner G(2023)Approximating weakly preferred semantics in abstract argumentation through vacuous reduct semanticsProceedings of the 20th International Conference on Principles of Knowledge Representation and Reasoning10.24963/kr.2023/11(107-116)Online publication date: 2-Sep-2023
https://dl.acm.org/doi/10.24963/kr.2023/11
Rodrigues OHong JLanperne MPark JCerny TShahriar H(2023)Representing and Manipulating Large Sequences of Argumentation LabellingsProceedings of the 38th ACM/SIGAPP Symposium on Applied Computing10.1145/3555776.3577756(995-1002)Online publication date: 27-Mar-2023
https://dl.acm.org/doi/10.1145/3555776.3577756
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Index Terms

SCC-recursiveness: a general schema for argumentation semantics
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
      1. Nonmonotonic, default reasoning and belief revision
      2. Semantic networks
2. Theory of computation
  1. Theory and algorithms for application domains
    1. Machine learning theory
      1. Inductive inference

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Published In

cover image Artificial Intelligence

Artificial Intelligence Volume 168, Issue 1-2

October, 2005

215 pages

ISSN:0004-3702

Issue’s Table of Contents

Copyright © Elsevier B.V. © 2005.

Publisher

Elsevier Science Publishers Ltd.

United Kingdom

Publication History

Published: 01 October 2005

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Cited By

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
Bl�mel LThimm MMarquis PSon TKern-Isberner G(2023)Approximating weakly preferred semantics in abstract argumentation through vacuous reduct semanticsProceedings of the 20th International Conference on Principles of Knowledge Representation and Reasoning10.24963/kr.2023/11(107-116)Online publication date: 2-Sep-2023
https://dl.acm.org/doi/10.24963/kr.2023/11
Rodrigues OHong JLanperne MPark JCerny TShahriar H(2023)Representing and Manipulating Large Sequences of Argumentation LabellingsProceedings of the 38th ACM/SIGAPP Symposium on Applied Computing10.1145/3555776.3577756(995-1002)Online publication date: 27-Mar-2023
https://dl.acm.org/doi/10.1145/3555776.3577756
Liu XChen WDignum FLomuscio AEndriss UNow� A(2021)Solid Semantics and Extension Aggregation Using Quota Rules under Integrity ConstraintsProceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3463952.3464169(1590-1592)Online publication date: 3-May-2021
https://dl.acm.org/doi/10.5555/3463952.3464169
Gaggl SRudolph SStra� H(2021)On the Decomposition of Abstract Dialectical Frameworks and the Complexity of Naive-based SemanticsJournal of Artificial Intelligence Research10.1613/jair.1.1134870(1-64)Online publication date: 1-May-2021
https://dl.acm.org/doi/10.1613/jair.1.11348
Alfano GGreco SParisi F(2019)An efficient algorithm for skeptical preferred acceptance in dynamic argumentation frameworksProceedings of the 28th International Joint Conference on Artificial Intelligence10.5555/3367032.3367036(18-24)Online publication date: 10-Aug-2019
https://dl.acm.org/doi/10.5555/3367032.3367036
Alfano GGreco SParisi FHung CPapadopoulos G(2019)On scaling the enumeration of the preferred extensions of abstract argumentation frameworksProceedings of the 34th ACM/SIGAPP Symposium on Applied Computing10.1145/3297280.3297393(1147-1153)Online publication date: 8-Apr-2019
https://dl.acm.org/doi/10.1145/3297280.3297393
Amgoud LBesnard P(2019)A formal characterization of the outcomes of rule-based argumentation systemsKnowledge and Information Systems10.1007/s10115-018-1227-561:1(543-588)Online publication date: 1-Oct-2019
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Guerrero ENieves JSandlund MLindgren H(2018)Activity qualifiers using an argument-based constructionKnowledge and Information Systems10.1007/s10115-017-1112-754:3(633-658)Online publication date: 1-Mar-2018
https://dl.acm.org/doi/10.1007/s10115-017-1112-7
Kr�ll MPichler RWoltran S(2017)On the complexity of enumerating the extensions of abstract argumentation frameworksProceedings of the 26th International Joint Conference on Artificial Intelligence10.5555/3171642.3171805(1145-1152)Online publication date: 19-Aug-2017
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