Toward Artificial Argumentation

AI Magazine

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.

There are numerous possible approaches to the phenomena of argumentation, all of which fall into one of three general categories:

Behavioral and Brain Sciences, 2011

Mercier and Sperber suggest that human reasoning is reflective and has evolved to support social interaction. Cognitive agents benefit from being able to reflect on their beliefs whether they are acting socially or alone. A formal framework for argumentation has emerged from research on artificial cognitive systems that parallels M&S's proposals, and may shed light on mental processes that underpin social interactions.

Science & technology education library, 2007

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2012

We discuss the value of argumentation in reaching agreements, based on its capability for dealing with conflicts and uncertainty. Logic-based models of argumentation have recently emerged as a key topic within Artificial Intelligence. Key reasons for the success of these models is that they are akin to human models of reasoning and debate, and their generalisation to frameworks for modelling dialogues. They therefore have the potential for bridging between human and machine reasoning in the presence of uncertainty and conflict. We provide an overview of a number of examples that bear witness to this potential, and that illustrate the added value of argumentation. These examples amount to methods and techniques for argumentation to aid machine reasoning (e.g. in the form of machine learning and belief functions) on the one hand and methods and techniques for argumentation to aid human reasoning (e.g. for various forms of decision making and deliberation and for the Web) on the other....

In this paper a tentative explanation of the competence of argumentation from an evolutionary point of view is offered. Because in contemporary argumentation theory and the informal logic approach the evolutionary perspective has been neglected, this paper gives an initial overview on the matter with the hope that core aspects of the argumentative faculty—such as argumentative normativity, the function of arguments, or fallacious moves, among others—can be seen differently afterwards. In order to specify the proposal, the main concepts considered are the notion of collective intentionality, cooperation, reputation, niche construction and, of course, basic evolutionary terms.

IEEE Intell. Informatics Bull., 2016

Developing systems that are aware of, and accommodate for, the cognitive capabilities and limitations of human users is emerging as a key characteristic of a new paradigm of cognitive computing in Artificial Intelligence. According to this paradigm, the behavior of such cognitive systems is modeled on the behavior of human personal assistants, able to understand the motivations and personal likings / affinities of their interlocutors, while also being able to explain, and ultimately persuade the latter about, their computed solution (e.g., a proposed action) to a problem. This paper examines the link between argument and cognition from the psychological and the computational perspectives, and investigates how the synthesis of work on reasoning and narrative text comprehension from Cognitive Psychology and of work on computational argumentation from AI can offer a scientifically sound and pragmatic basis for building human-aware cognitive systems for everyday tasks. The paper aims, t...

D. Walton and D. M. Godden, in Considering Pragma-Dialectics, ed. Peter Houtlosser and Agnes van Rees, Mahwah, New Jersey, Erlbaum, 2006, 287-299.

The research of the Amsterdam School has spread outward across the discipline of argumentation studies like a new day, awakening us to new vistas, casting light on new opportunities, and offering a fresh look at our familiar surroundings. Over the years this approach has proved so remarkably effective that many of its central tenets have been widely recognized and accepted.

Thinking & Reasoning, 2012

Although argumentation plays an essential role in our lives, there is no integrated area of research on the psychology of argumentation. Instead research on argumentation is conducted in a number of separate research communities that are spread across disciplines and have only limited interaction. With a view to bridging these different strands, we first distinguish between three meanings of the word ''argument'': argument as a reason, argument as a structured sequence of reasons and claims, and argument as a social exchange. All three meanings are integral to a complete understanding of human reasoning and cognition. Cognitive psychological research on argumentation has focused mostly on the first and second of these meanings, so we present perspectives on argumentation from outside of cognitive psychology, which focus on the second and third. Specifically, we give an overview of the methods, goals, and disciplinary backgrounds of research on the production, the analysis, and the evaluation of arguments. Finally, in introducing the experimental studies included in this special issue, which were conducted by researchers from a range of theoretical backgrounds, we underline the breadth of argumentation research as well as stress opportunities for mutual awareness and integration.