In this chapter a compendium of all the schemes discussed is given, along with the source of the scheme in the argumentation literature. We have tried to make the compendium most useful to the reader by presenting the schemes that represent the most commonly used forms of argument, including not only those used in everyday discourse, but also certain schemes that are important in legal and scientific reasoning. Many of these schemes have subtypes, and research on the classification of the subtypes, and even more generally, research on determining which schemes are subspecies of other schemes, is not yet at an advanced stage. Thus while we have made occasional remarks on these matters, hoping to provide some insight, we have not generally listed all the known subspecies of the schemes. There are two especially important exceptions that need to be noted.

We have included a fairly comprehensive account of the known subschemes of the argument from popular opinion, to give the reader an idea of how it can be important to recognize many of these different subschemes in dealing with common arguments of the type associated with informal fallacies. The other important exception is the case of the argumentum ad hominem. Many subschemes for this type of argument have been recognized, and much work on trying to organize and classify them has been conducted (Walton, 1998).

It would be very helpful for users of the schemes to have a more refined system of classification, so that the user could search through to find a scheme applicable to her needs in a given case by searching under other, more general ones where the particular scheme being sought is known to fit. It is already fairly evident from the compendium of schemes that some schemes fit under others as subspecies of them. For example, one of the most common schemes is argument from consequences. It is closely related to practical reasoning. Other schemes, like those for the slippery slope argument, often fit under the category of argument from consequences. However, such classifications are not as straightforward as they initially seem. For example, some slippery slope arguments fit under the category of arguments from precedent, and therefore may not fit the scheme of argument from consequences, at least in any straightforward way. Another very common scheme under which many others fit as subspecies is the scheme for argument from commitment. Here we have a cluster of schemes that are closely related to each other, but in complex ways. Schemes that are very general, like those for argument from consequences and argument from ignorance, are related to many other, more specific schemes that fall under them. This chapter sets us on the road to beginning the research project of taking such clusters of schemes and investigating how they fit together with their neighboring schemes.

In this chapter, we outline a number of schemes that do not fall into any single classification but are useful to know about before considering the schemes discussed in the next chapters. We begin with a group of schemes based on assumptions about knowledge and go on to consider a group related to actions, goals, and means. These latter include schemes representing practical reasoning and arguing from the consequences of an action that is being considered. Finally, we consider some other schemes that are not easily classified, including arguments from composition and division, fear appeal arguments, appeals to pity, and argument from alternatives and opposites. Some work has been done on some of these schemes, while others remain largely unstudied.

ARGUMENTS FROM KNOWLEDGE

In arguments from expert opinion, position to know, and witness testimony, the acceptability of the conclusion is drawn from a knowledge base that the source is assumed to have access to. The relation between the latter and the plausibility of the conclusion is based on a kind of default reasoning: it is assumed that the proposition in question is contained in a certain subject domain that is known by the source. For this reason, it is an assumption in this kind of argumentation that many or most of the true propositions of the domain are known. The warrant of this kind of argumentation is therefore closely similar to that of the argument from ignorance.

Argumentation theory has laid foundations for and has had influence upon a wide variety of computational systems (Reed and Norman, 2003). This chapter explores four distinct areas, reviewing the ways in which argumentation schemes have been put to work: in natural language generation, in interagent communication, in automated reasoning, and in various specific computational applications. To start, however, we look at the tools that are being used to support the development of these applications and that allow the creation, analysis, and manipulation of the raw computational resources that involve argumentation schemes.

SCHEMES IN ARAUCARIA

Following work examining the diagramming of natural argument – an important topic from the practical, pedagogic point of view (van Gelder and Rizzo, 2001), but also a driver of theoretical development in informal logic (Walton & Reed, 2004) – Reed and Rowe (2004) developed Araucaria, a system for aiding human analysts and students in marking up argument. Araucaria adopts the “standard treatment” (Freeman, 1991) for argument analysis, based on identification of propositions (as vertices in a diagram) and the relationships of support and attack holding between them (edges in a diagram). It is thus similar to a range of argument visualization tools (see Kirschner et al., 2003, for an overview), and familiar from AI techniques such as Pollock's (1995) inference graphs and even Bayesian nets and qualitative probabilistic networks.

This chapter introduces the reader to argumentation schemes and explains, through the use of some examples, why they are important. Another aim of the chapter is to briefly review the literature on argumentation schemes, including the key works by Hastings, Walton, and Kienpointner, and to set it in a broader context, bringing out some characteristics of defeasible reasoning and argument evaluation that are fundamental to the study of schemes. Another is to introduce the beginning reader to some basic tools, like argument diagramming, that utilize schemes and need to be integrated with them. In this chapter we will introduce the reader to an automated system of argument diagramming called Araucaria. This technique is a box-and-arrow representation of the premises and conclusions of an argument, showing how one argument can be chained together with others to form a sequence of reasoning. This tool will be used in subsequent chapters, and so we need to introduce the reader to it now. One of our goals in the book is to show how argumentation schemes are in the process of being modeled by argument technology in the field of artificial intelligence (AI). However, we will reserve our fullest account of these developments for the last chapter of the book, even though, from time to time, we will mention aspects of them that impinge on our fundamental understanding of argumentation schemes as forms of reasoning.