Toward Artificial Argumentation
Open accessAbstract
The field of computational models of argument is emerging as an important aspect of artificial intelligence research. The reason for this is based on the recognition that if we are to develop robust intelligent systems, then it is imperative that they can handle incomplete and inconsistent information in a way that somehow emulates the way humans tackle such a complex task. And one of the key ways that humans do this is to use argumentation either internally, by evaluating arguments and counterarguments, or externally, by for instance entering into a discussion or debate where arguments are exchanged. As we report in this review, recent developments in the field are leading to technology for artificial argumentation, in the legal, medical, and e‐government domains, and interesting tools for argument mining, for debating technologies, and for argumentation solvers are emerging.
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A lot of work has been done on argumentation and dialog games, but the focus in these areas is generally the logical structure of the framework to express and to relate arguments or the protocol to exchange arguments.
“A lot of work has also been done on argumentation and dialog games [6, 11, 51, 53] but the focus in these areas is generally the logical structure of the framework to express and to relate arguments or the protocol to exchange arguments.”
From Beyond explainability: justifiability and contestability of algorithmic decision systems (2022) · cites this paper as [6]
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References 22 · Cited by 142
Research works printed but not linked: 6
- [APL + 14] E. Aharoni, A. Polnarov, T. Lavee, D. Hershcovich, R. Levy, R. Rinott, D. Gutfreund, and N. Slonim. A benchmark dataset for automatic detection of claims and evidence in the context of controversial topics. In Proceedings of the First Workshop on Argumentation Mining , pages 64-68. Association for Computational Linguistics, 2014.
- [GKSS08] C. Gomes, H. Kautz, A. Sabharwal, and B. Selman. Satisfiability solvers. In F. Van Harmelen, V. Lifschitz, and B. Porter, editors, Handbook of Knowledge Representation , page 89134. Elsevier, 2008.
- [PM11] R. Mochales Palau and M-F Moens. Argumentation mining. Artificial Intelligence in Law , 19(1):1-22, 2011.
- [RR04] C. Reed and G. Rowe. Araucaria: Software for argument analysis, diagramming and representation. International Journal on Artificial Intelligence Tools , 13(4):983, 2004.
- [RS09] I. Rahwan and G. Simari, editors. Argumentation in Artificial Intelligence . Springer, 2009.
- [SG14] C. Stab and I. Gurevych. Identifying argumentative discourse structures in persuasive essays. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, (EMNLP'14) , pages 46-56, 2014.
- Authors
- Atkinson, K., Baroni, P., Giacomin, M., Hunter, A., Prakken, H., Reed, C., Simari, G., Thimm, M., & Villata, S.
- Affiliations
- University of Liverpool (GB)
- University of Brescia (IT)
- University College London (GB)
- University of Groningen (NL)
- University of Dundee (GB)
- Universidad Nacional del Sur (AR)
- University of Koblenz and Landau (DE)
- Université Côte d'Azur (FR)
- ORCID
- Venue
- AI Magazine
- Publisher
- Wiley
- Published
- 2017-09
- Volume
- 38
- Issue
- 3
- Pages
- 25-36
- ISSN
- 0738-4602 (ISSN-L)
- 2371-9621
- OpenAlex
- W2761833367
- Cited by
- 142
- References
- 22
- Citations by year
- 2026: 13 · 2025: 13 · 2024: 16 · 2023: 9 · 2022: 11 · 2021: 27 · 2020: 27 · 2019: 15 · 2018: 11
- FWCI
- 8.65
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- AI Magazine (publishedVersion, cc-by)
- Discovery Research Portal (University of Dundee) (submittedVersion, other-oa)
- HAL (submittedVersion)
- Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
- UCL Discovery (University College London) (submittedVersion)
- Institutional Research Information System (Università degli Studi di Brescia) (submittedVersion)
- Funders
- Universidad Nacional del Sur
- Horizon 2020 Framework Programme (690974)
- Engineering and Physical Sciences Research Council (EP/N008294/1, H2020, EP/N014871/1, EP/G060347/1)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Multi-Agent Systems and Negotiation
- Physical Sciences › Computer Science › Artificial Intelligence › Logic, Reasoning, and Knowledge
- Social Sciences › Political Science and International Relations › Artificial Intelligence in Law
- Keywords
- incomplete information, data inconsistency, argument mining, legal reasoning, medical reasoning, e-government
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