Argument Structure Models and Visualization

Argument Structure Models and Visualization

Ephraim Nissan (Goldsmith’s College of the University of London, UK)
DOI: 10.4018/978-1-60566-014-1.ch011
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In order to visualize argumentation, there exist tools from multimedia. The most advanced sides of computational modeling of arguments belong in models and tools upstream of visualization tools: the latter are an interface. Computer models of argumentation come in three categories: logic-based (highly theoretical), probablistic, and pragmatic ad hoc treatments. Theoretical formalisms of argumentation were developed by logicists within artificial intelligence (and were implemented and often can be reused outside the original applications), or then the formalisms are rooted in philosophers’ work. We cite some such work, but focus on tools that support argumentation visually. Argumentation turns out in a wide spectrum of everyday life situations, including professional ones. Computational models of argumentation have found application in tutoring systems, tools for marshalling legal evidence, and models of multiagent communication. Intelligent systems and other computer tools potentially stand to benefit as well. Multimedia are applied to argumentation (in visualization tools), and also are a promising field of application (in tutoring systems). The design of networks could potentially benefit, if communication is modeled using multiagent technology.
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Background Concepts: Kinds And Levels Of Argumentation

Argumentation is the activity of putting arguments for or against something. [...] In purely speculative matters, one adduces arguments for or against believing something about what is the case. In practical contexts, one adduces arguments which are either reasons for or against doing something, or reasons for or against holding an opinion about what ought to be or may be or can be done (MacCormick, 1995, pp. 467-468).

A reason given for acting or not acting in a certain way may be on account of what so acting or not acting will bring about. Such is teleological reasoning. All teleological reasoning presupposes some evaluation (MacCormick, 1995, p. 468).

In contrast, “Deontological reasoning appeals to principles of right or wrong [...] taken to be ultimate, not derived from some form of teleological reasoning” (MacCormick, 1995, p. 468). Systemic arguments are kinds of “arguments which work towards an acceptable understanding of a legal text seen particularly in its context as part of a legal system” (p. 473), for example, the argument from precedent, the argument from analogy, and so forth.

Prakken and Sartor (2002, Section 1.2) usefully

Key Terms in this Chapter

Deontic, Deontology: Pertaining to duty and permissibility. Deontic logic has operators for duty. Deontological arguments appeal to principles of right or wrong, ultimate (rather than teleological) principles about what must or ought, or must not or ought not to be or be done.

Adversary Argument: “[N]either participant expects to persuade or be persuaded: The participants intend to remain adversaries, and present their arguments for the judgment of an audience (which may or may not actually be present). In these arguments, an arguer’s aim is to make his side look good while making the opponent’s look bad” (Flowers et al., 1982, p. 275). The ABDUL/ILANA program models such arguers (ibid.).

Teleological: Of an argument (as opposed to deontological reasoning): of a “reason given for acting or not acting in a certain way may be on account of what so acting or not acting will bring about. [...] All teleological reasoning presupposes some evaluation” (MacCormick, 1995, p. 468).

Argumentation: How to put forth propositions in support or against something. An established field in rhetoric, within AI & Law it became a major field during the 1990s.

Persuasion Argument: The participants in the dialogue are both willing to be persuaded as well as trying to persuade. This is relevant for computer tools for supporting negotiation.

Anchored Narratives: The theory of anchored narratives was proposed by Wagenaar et al. (1993): narrative is related to evidence by a connection (or anchor), but this is a background generalization, which, critics remarked, only holds heuristically.

Wigmore Charts: A graphic method of structuring legal arguments, currently fairly popular among legal evidence scholars; originally devised in the early 20th century.

Abductive Inference: Inference to the “best” explanation. It departs from deductive inference.

AI & Law: Artificial intelligence as applied to law, this being an established discipline both within legal computing and within artificial intelligence.

Generalizations: Or background knowledge, or empirical generalizations: common sense heuristic rules, which apply to a given instance a belief, held concerning a pattern, and are resorted to when, interpreting the evidence and reconstructing a legal narrative for argumentation in court.

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