Alison Chorley

Persuasion and Value in Legal Argument

In this paper we consider legal reasoning as a species of practical reasoning. As such it is important both that arguments are considered in the context of competing, attacking and supporting arguments, and that the possibility of rational disagreement is accommodated. We present two formal frameworks for considering systems of arguments: the standard framework of Dung, and an extension which relates arguments to values allowing for rational disagreement. We apply these frameworks to modelling a body of case law, explain how the frameworks can be generated to reconstruct legal reasoning in particular cases, and describe some tools to support the extraction of the value related knowledge required from a set of precedent cases.

An empirical investigation of reasoning with legal cases through theory construction and application

In recent years several proposals to view reasoning with legal cases as theory construction have been advanced. The most detailed of these is that of Bench-Capon and Sartor, which uses facts, rules, values and preferences to build a theory designed to explain the decisions in a set of cases. In this paper we describe CATE (CAse Theory Editor), a tool intended to support the construction of theories as described by Bench-Capon and Sartor, and which produces executable code corresponding to a theory. CATE has been used in a series of experiments intended to explore a number of issues relating to such theories, including how the theories should be constructed, how sets of values should be compared, and the representation of cases using structured values as opposed to factors.

AGATHA: using heuristic search to automate the construction of case law theories

In this paper we describe AGATHA, a program designed to automate the process of theory construction in case based domains. Given a seed case and a number of precedent cases, the program uses a set of argument moves to generate a search space for a dialogue between the parties to the dispute. Each move is associated with a set of theory constructors, and thus each point in the space can be associated with a theory intended to explain the seed case and the other cases in the domain. The space is large and so an heuristic search method is needed. This paper describes two methods based on A* and alpha/beta pruning and also a series of experiments designed to explore the appropriateness of different evaluation functions, the most useful precedents to use as seed cases and the quality of the resulting theories.

Developing legal knowledge based systems through theory construction

In this note we report a project exploring the notion of reasoning with legal cases as a process of theory construction, evaluation and application, as described in work by Bench-Capon and Sartor.

AGATHA: automated construction of case law theories through heuristic search

In this paper we describe AGATHA, a program designed to automate the process of theory construction in case based domains. Given a seed case and a number of precedent cases, the program uses a set of argument moves to generate a search space for a dialogue between the parties to the dispute. Each move is associated with a set of theory constructors, and thus each point in the space can be associated with a theory intended to explain the seed case and the other cases in the domain. The space is large, and so a heuristic search method based on A* is used to guide the selection of moves and precedent cases. The paper describes a series of experiments designed to explore the appropriateness of different evaluation functions, the most useful precedents and the quality of the resulting theories.

Support for Constructing Theories in Case Law Domains

Reasoning with cases has been a central focus of work in Artificial Intelligence and Law since the field began in the late eighties. Reasoning with cases is a distinctive feature of legal reasoning and is of interest because such reasoning is both inherently defeasible, and because it is an example of practical reasoning in that it aims to provide a rational basis for a choice rather than to deduce some conclusion from premises. As reasoning with cases has developed, it has moved beyond techniq ues for matching past cases to the current situation to consider how arguments for a position are constructed on the basis of past cases. Recently it has been argued that this should be seen as a process involving the construction, evaluation and applicati on of theories grounded in the phenomena presented by the past cases. Our aim is to develop and refine this idea, with the ultimate goal of building a system which is able to reason with cases in this manner. This paper describes the implementation of a th eory con-struction tool (CATE) to aid in the construction and evaluation of theories to explain the decisions obtained in legal cases, so as to give an understanding of a body of case law. CATE gives a rapid way of creating and testing different theories. Use of CATE is illustrated by showing the construction of alternative theories in a small case study. CATE is useful in itself for anyone wishing to explore their understanding of a set of cases, such as lawyers practising in the domain and knowledge engine ers tasked with constructing a rule based system in the domain. We also believe that it offers good prospects for automating the process of theory construction.