In this paper we discuss a hybrid approach combining Case-Based Reasoning (CBR) .

We discuss several aspects of legal arguments, primarily arguments about the meaning of statutes. First, we discuss how the requirements of argument guide the specification and selection of supporting cases and how an existing case base influences argument formation.

We focus on realistic, complex domains where the concepts, terms and predicates used by domain rules or by rule-based models are not well-defined. Often, in such inherently ill-defined domains the rules do not encompass all the situations they are asked or assumed to cover, admit tacit exceptions, or can be contradicted and annulled by other rules. Interpretation is therefore required of the terms and predicates used. The law is a prototypical example of such an area, where terms used in legal statutes are not completely defined by legal regulations. The use of case-based reasoning (CBR) to complement and supplement other types of reasoning involves many computational questions of system architecture and control. The key focus of this work is how and when to interleave CBR with other modes of reasoning in the context of applying a rule or model to a new set of facts in light of a corpus of cases of past application. The goal is to generate an explanation or argument as to how the new fact situation might be interpreted. In particular, we report on a system called CABARET (CAse-BAsed REasoning Tool), a hybrid architecture we have built to study and experiment with these issues.

This paper presents a hybrid case-based reasoning (CBR) and information retrieval (IR) system, called SPIRE, that both retrieves documents from a full-text document corpus and from within individual documents, and locates passages likely to contain information about important problem-solving features of cases. SPIRE uses two case-bases, one containing past precedents, and one containing excerpts from past case texts. Both are used by SPIRE to automatically generate queries, which are then run by the INQUERY full-text retrieval engine on a large text collection in the case of document retrieval and on individual text documents for passage retrieval.

In this paper, we consider a distinctly bottom-up which generates arguments by performing a heuristic approach.

Also to appear in Proceedings NIE--LRDC Conference on Thinking and Learning Skills, Lawrence Erlbaum Associates.

In mathematics, examples can be said to be as important to understanding as the traditionally exalted definitions, theorems, and proofs (Rissland 1978). In fact, some mathematical areas developed in response to troublesome counter-examples like modern real function theory which has been called'the branch of mathematics which deals with counter-examples" (Munroe 1953). In the law, examples -- that is, legal cases -- are the basis from which the law derives (at least in common law systems like those of the United States and England): the law is made through court decisions by consideration of specific problems in specific cases. The cases lead to rule-like decisions which are then refined (or perhaps refuted, i.e., overturned) in subsequent cases. In linguistics, for instance in the study of syntax, linguistic rules are derived from study of examples of actual language and are then subjected to testing on more examples. Some examples are taken from the infinite store of run of the mill sentences available to every natural speaker; others, like certain difficult garden path sentences, are fabricated and used as counter-examples are in mathematics.

For example, if the game is chess, the piece may be: king, rook, pawn... My aim was to realize a program playing several For some games, all men are of the same games.

A general game-playing program must know the rules of the particular playing game. These rules are: (1) an algorithm indicating the winning state; (2) an algorithm enumerating legal moves. A move gives a set of changes from the present situation. There are two means of giving these rules: (1) We can write a subroutine which recognizes if we have won and another which enumerates legal moves. Such a subroutine is a black box giving to the calling program the answer: 'you win' or'you do not win', or the list of legal moves. But it cannot know what is in that subroutine.

I] presented a systematic account of the facts of thought and of the methods to express them. But if we do not restrict the domain, there are too many things to be considered. Brunot accurately studied various ways to express surprise, prices, anteriority in the future, a question... But concepts used only in specific domains do not appear in his book. That is why I chose a technical domain -- annotations of chess games -- and I tried to fmd what was said in that domain.