Toward Artificial Argumentation

By Atkinson, Katie; Baroni, Pietro et al. | AI Magazine, Fall 2017 | Go to article overview

Toward Artificial Argumentation


Atkinson, Katie, Baroni, Pietro, Giacomin, Massimiliano, Hunter, Anthony, Prakken, Henry, Reed, Chris, Simari, Guillermo, Thimm, Matthias, Villata, Serena, AI Magazine


Humans argue.1 This distinctive feature is at the same time an important cognitive capacity and a powerful social phenomenon. It has attracted attention and careful analysis since the dawn of civilization, being intimately related to the origin of any form of social organization, from political debates to law, and of structured thinking, from philosophy to science and arts.

As a cognitive capacity, argumentation is important for handling conflicting beliefs, assumptions, viewpoints, opinions, goals, and many other kinds of mental attitudes. When we are faced with a situation where we find that our information is incomplete or inconsistent, we often resort to the use of arguments in favor and against a given position in order to make sense of the situation. When we interact with other people we often exchange arguments in a cooperative or competitive fashion to reach a final agreement or to defend and promote an individual position.

Occurring continuously both in our mind and in the social arena, argumentation pervades our intelligent behavior and the challenge of developing artificial argumentation systems appears to be as diverse and exciting as the challenge of artificial intelligence itself.

Indeed, this rich and important phenomenon offers an opportunity to develop models and tools for argumentation and to conceive autonomous artificial agents that can exploit these models and tools in the cognitive tasks they are required to carry out. To this purpose, a number of interesting lines of research are being investigated within artificial intelligence and several neighbor fields, leading to the establishment of computational models of argument as a promising interdisciplinary research area. Progress in this area is expected to contribute to significant advances in the understanding and modeling of various aspects of human intelligence.

In this article, we review formalisms for capturing various aspects of argumentation, and we present advances in their applications, with the aim to communicate how research is making progress toward the goal of making artificial argumentation technologies and systems a mature and widespread reality. In this brief review, we are unable to discuss or cite all the relevant literature, and we suggest that the interested reader seek more detailed coverage of the foundations from Rahwan and Simari (2009), of applications from Modgil et al. (2013), and of recent developments from the proceedings of the International Conference on Computational Models of Argument series,2 and the Argument and Computation journal.3

Models of Argument

Computational models of argument are being developed to reflect aspects of how humans build, exchange, analyze, and use arguments in their daily lives to deal with a world where the information may be controversial, incomplete, or inconsistent (BenchCapon and Dunne 2007, Rahwan and Simari 2009). The diversity of the manifestations of arguments in real life implies diversity in the relevant models too and the impossibility to reduce the vast available literature to a single reference scheme. It is possible however to identify some layers that can be regarded as basic building blocks for the construction of an argumentation model. Specific modeling approaches may differ in the selection of which layers they actually use, in the way the selected layers are combined, and in the formalization adopted within each layer.

We consider the following five main layers: structural, relational, dialogical, assessment, and rhetorical. They are described in the following and also summarized in Figure 1. Note that while each layer has its own nature and distinctive traits, the boundaries between layers may not be so neat in some contexts, and specific formalisms may inextricably merge together aspects relevant to different layers.

Structural Layer

This layer concerns the structure of the arguments and how they are built: essentially it specifies, in a given context, what an argument looks like, in terms of its internal structure, and which are the ingredients for its construction. …

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