Abstract. In this paper we explore the thesis that the role of argumentation in practical reasoning in general and legal reasoning in particular is to justify the use of defeasible rules to derive a conclusion in preference to the use of other defeasible rules to derive a conflicting conclusion. The defeasibility of rules is expressed by means of non-provability claims as additional conditions of the rules. We outline an abstract approach to defeasible reasoning and argumentation which includes many existing formalisms, including default logic, extended logic programming, non-monotonic modal logic and auto-epistemic logic, as special cases. We show, in particular, that the “admissibility ” semantics for all these formalisms has a natural argumentationtheoretic interpretation and proof procedure, which seem to correspond well with informal argumentation. In the admissibility semantics there is only one way for one argument to attack another, namely by undermining one of its non-provability claims. In this paper, we show how other kinds of attack between arguments, specifically how rebuttal and priority attacks, can be reduced to the undermining of non-provability claims. 1.

Argumentation theory involves the analysis of naturally occurring argument, and one key tool employed to this end both in the academic community and in teaching critical thinking skills to undergraduates is argument diagramming. By identifying the structure of an argument in terms of its constituents and the relationships between them, it becomes easier to critically evaluate each part of an argument in turn. The task of analysis and diagramming, however, is labor intensive and often idiosyncratic, which can make academic exchange difficult. The Araucaria system provides an interface which supports the diagramming process, and then saves the result using AML, an open standard, designed in XML, for describing argument structure. Araucaria aims to be of use not only in pedagogical situations, but also in support of research activity. As a result, it has been designed from the outset to handle more advanced argumentation theoretic concepts such as schemes, which capture stereotypical patterns of reasoning. The software is also designed to be compatible with a number of applications under development, including dialogic interaction and online corpus provision. Together, these features, combined with its platform independence and ease of use, have the potential to make Araucaria a valuable resource for the academic community.

In recent years we have witnessed the wide-spread evolution of support tools that operate in association with the user to accomplish a range of computer-mediated tasks. Two examples of these tools are critics and recommenders. Critics are cooperative tools that observe the user interacting with a computer system and present reasoned opinions about a product under development. Recommender systems are tools that assist users by facilitating access to relevant items. At the same time, defeasible argumentation has evolved as a successful approach in AI to model commonsense qualitative reasoning, with applications in many areas, such as agent theory, knowledge engineering and legal reasoning. This paper presents a novel approach towards the integration of user support systems, such as critics and recommender systems, with a defeasible argumentation framework. The final goal is to enhance practical reasoning capabilities of current user support tools by incorporating argument-based qualitative inference.

Recommender systems have evolved in the last years as specialized tools to assist users in a plethora of computermediated tasks by providing guidelines or hints. Most recommender systems are aimed at facilitating access to relevant items, a situation particularly common when performing web-based tasks. At the same time, defeasible argumentation has evolved as a successful approach in AI to model commonsense qualitative reasoning, with applications in many areas, such as agent theory, knowledge engineering and legal reasoning. This paper presents a first approach towards the integration of web-based recommender systems with a defeasible argumentation framework. The final goal is to enhance practical reasoning capabilities of current recommender system technology by incorporating argument-based qualitative inference.

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This paper presents a theory of reasoning with evidence in order to determine the facts in a criminal case. The focus is on the process of proof, in which the facts of the case are determined, rather than on related legal issues, such as the admissibility of evidence. In the literature, two approaches to reasoning with evidence can be distinguished, one argument-based and one storybased. In an argument-based approach to reasoning with evidence, the reasons for and against the occurrence of an event, e.g., based on witness testimony, are central. In a story-based approach, evidence is evaluated and interpreted from the perspective of the factual stories as they may have occurred in a case, e.g., as they are defended by the prosecution. In this paper, we argue that both arguments and narratives are relevant and useful in the reasoning with and interpretation of evidence. Therefore a hybrid approach is proposed and formally developed, doing justice to both the argumentbased and the narrative-based perspective. By the formalization of the theory and the associated graphical representations, our proposal is the basis for the design of software developed as a tool to make sense of the evidence in complex cases.

work contained in this document has been submitted in support of an application for a degree or qualification of this or any other university or other institution of learning. All verbatim extracts have been distinguished by quotation marks, and all sources of information have been specifically acknowledged. Signed: Date: 2007 In this thesis we present a framework for argument which aims to support concepts useful for evi-dential reasoning. The framework is presented at two levels, an abstract level, in which arguments are not treated as concrete entities, and a concrete level, in which arguments are underpinned by Subjective Logic. At the abstract level, the framework provides the theoretical underpinnings for the concept of support in a manner distinct from other frameworks. Support for an argument can mean that the argument may be inferred from existing arguments, or that the argument is a prima facie argument. At the concrete level, support for burden of proof, argument schemes and sensing actions is introduced. A simple dialogue game is also presented, which shows how agents can

In this article the argumentation structure of the court’s decision in the Popov v. Hayashi case is formalised in (Prakken, 2009)’s abstract framework for argument-based inference with structured arguments. In this framework, arguments are inference trees formed by applying two kinds of inference rules, strict and defeasible rules. Arguments can be attacked in three ways: attacking a premisse, attacking a conclusion and attacking an inference. To resolve such conflicts, preferences may be used, which leads to three corresponding kinds of defeat, after which (Dung, 1995)’s abstract acceptability semantics can be used to evaluate the arguments. In the present paper the abstract framework is instantiated with strict inference rules corresponding to first-order logic and with defeasible inference rules for defeasible modus ponens and various argument schemes. The main techniques used in the formal reconstruction of the case are rule-exception structures and arguments about rule validity. Arguments about socio-legal values and the use of precedent cases are reduced to arguments about rule validity. The tree structure of arguments, with explicit subargument relations between arguments, is used to capture the dependency relations between the elements of the court’s decision. 1

Abstract. While researchers have looked at many aspects of argumentation, an area often neglected is that of argumentation strategies. That is, given multiple possible arguments that an agent can put forth, which should be selected in what circumstances. In this paper, we propose a heuristic that implements one such strategy. The heuristic assigns a utility cost to revealing information, as well as a utility to winning, drawing and losing an argument. An agent participating in a dialogue then attempts to maximise its utility. After informally presenting the heuristic, we discuss some of its novel features, after which some avenues for future work are examined. 1

While researchers have looked at many aspects of argumentation, an area often neglected is that of argumentation strategies. That is, given multiple possible arguments that an agent can put forth, which should be selected in what circumstances. In this paper, we propose a heuristic that implements one such strategy, namely revealing as little information as possible to other dialogue participants. After formalising the concept and presenting a simple argumentation framework in which it can be used, we show a sample dialogue utilising the heuristic. We conclude by exploring ways in which this heuristic can be employed and a discussion of future work is made which will allow for the use of our approach in more complicated, realistic dialogues.