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Interfaces to Formal Argumentation

Dr. Federico Cerutti

Like other systems for automatic reasoning, argumentation approaches can suffer from “opacity.” We explore one of the few mixed approaches explaining, in natural language, the structure of arguments to ensure an understanding of their acceptability status. In particular, we will summarise the results described in [1], in which we assessed, by means of an experiment, the claim that computational models of argumentation provide support for complex decision making activities in part due to the close alignment between their semantics and human intuition. Results show a correspondence between the acceptability of arguments by human subjects and the justification status prescribed by the formal theory in the majority of the cases. However, post-hoc analyses show that there are some deviations. This seems to suggest that there is the need for some effort for making formal argumentation process more transparent. We will also illustrate some ongoing works [2] and discuss connections with argument mining and the need for rich annotation techniques, as presented in [3]. 
References
[1] Federico Cerutti, Nava Tintarev, and Nir Oren. Formal Arguments, Preferences, and Natural Language Interfaces to Humans: an Empirical Evaluation. In 21st European Conference on Artificial Intelligence, pages 207–212, 2014.
[2] Federico Cerutti, Alice Toniolo, Timothy J. Norman: On Natural Language Generation of Formal Argumentation. CoRR abs/1706.04033 (2017)
[3] Federico Cerutti, Alexis Palmer, Ariel Rosenfeld, Jan Snajder, Francesca Toni: A Pilot Study in Using Argumentation Frameworks for Online Debates. SAFA@COMMA 2016: 63-74

30.11.2017 - 10:15
B 017