A fuzzy theoretical approach to case-based representation and inference in CISG

In a legal expert system based on CBR (Case-Based Reasoning), legal statute rules are interpreted on the basis of precedents. This interpretation, because of its vagueness and uncertainty of the interpretation cannot be handled with the means used for crisp cases. In our legal expert system, on the basis of the facts of precedents, the statute rule is interpreted as a form of case rule, the application of which involves the concepts of membership and vagueness. The case rule is stored in a data base by means of fuzzy frames. The inference based on a case rule is made by fuzzy YES and fuzzy NO, and the degree of similarity of cases. The system proposed here will be used for legal education; its main area of application is contract, especially in relation to the United Nations Convention on Contracts for the International Sale of Goods (CISG).     

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.     

Deontic logic in the representation of law: Towards a methodology

There seems to be no clear consensus in the existing literature about the role of deontic logic in legal knowledge representation — in large part, we argue, because of an apparent misunderstanding of what deontic logic is, and a misplaced preoccupation with the surface formulation of legislative texts. Our aim in this paper is to indicate, first, which aspects of legal reasoning are addressed by deontic logic, and then to sketch out the beginnings of a methodology for its use in the analysis and representation of law.The essential point for which we argue is that deontic logic — in some form or other —needs to be taken seriously whenever it is necessary to make explicit, and then reason about, the distinction between what ought to be the case and what is the case, or as we also say, between the ideal and the actual. We take the library regulations at Imperial College as the main illustration, and small examples from genuinely legal domains to introduce specific points. In conclusion, we touch on the role of deontic logic in the development of the theory of normative positions.Deontic logic and the theory of normative positions are of relevance to legal knowledge representation, but also to the analysis and. representation of normative systems generally. The emphasis of the paper is on legal knowledge representation, but we seek to place the discussion within the context of a broader range of issues concerning the role of deontic logic in Computer Science.     

THE SCOPE OF DIMENSIONAL ANALYSIS IN QUALITATIVE REASONING

Dimensional analysis, traditionally used in physics and engineering to identify quantitative relationships, has recently been applied to qualitative reasoning of physical systems. We illustrate some problems of this approach. In the light of this, we reexamine the fundamentals of dimensional analysis in order to more precisely characterize its scope and limitations as a tool in qualitative reasoning. We also explore its relationship to state equation representations of physical systems. In particular, we describe its value in providing a set of constraints to reduce the ambiguity that bedevils qualitative reasoning schemes. We argue that dimensional analysis should not be seen as a substitute for knowledge about the physics but rather a supplement to other sources of knowledge.     

An Australian Perspective on Research and Development Required for the Construction of Applied Legal Decision Support Systems

At the Donald Berman Laboratory for Information Technology and Law, La TrobeUniversity Australia, we have been building legal decision support systems for a dozenyears. Whilst most of our energy has been devoted to conducting research in ArtificialIntelligence and Law, over the past few years we have increasingly focused uponbuilding legal decision support systems that have a commercial focus.In this paper we discuss the evolution of our systems. We begin with a discussion ofrule-based systems and discuss the transition to hybrid rule-based/case-based systems.We next discuss how we have used machine learning in building legal decision supportsystems. Our focus on using machine learning led us to investigate the domains ofexplanation and argumentation. We conclude by discussing our current work onbuilding negotiation support systems and tools for constructing web-based legaldecision support systems.     

灰度关联理论在CBR中的应用研究

针对基于规则推理技术（RBR）知识获取困难、自学习能力差等缺陷,将基于案例推理技术（CBR）引入故障诊断系统中。介绍了基于案例推理的故障诊断方法的工作机理和过程模型,阐述了案例表示、案例检索、案例保存和案例库维护机制,然后简单介绍了灰色关联理论知识,并把灰色关联理论应用到故障案例相似度的计算中。根据实验结果可知,该方法有效地改进了案例检索算法,提高了故障案例匹配的准确度和检索效率,同时具有较好的分辨率。     

Understanding Similarity: A Joint Project for Psychology, Case-Based Reasoning, and Law

Case-based Reasoning (CBR) began as a theory of human cognition, but has attracted relatively little direct experimental or theoretical investigation in psychology. However, psychologists have developed a range of instance-based theories of cognition and have extensively studied how similarity to past cases can guide categorization of new cases. This paper considers the relation between CBR and psychological research, focussing on similarity in human and artificial case-based reasoning in law. We argue that CBR, psychology and legal theory have complementary contributions to understanding similarity, and describe what each offers. This allows us to establish criteria for assessing existing CBR systems in law and to establish what we consider to be the crucial goals for further research on similarity, both from a psychological and a CBR perspective.     

The 6-49 Lottery Paradox

The paradox of the preface and the lottery paradox are paradoxes of practical certainty sharing certain features. The paradox of the lottery argues that rational agents are at once practically certain that each ticket in a lottery will lose but also practically certain some ticket will win. The paradox of the preface argues that rational agents are at once practically certain that all facts in a written volume are true, yet are also practically certain that some fact is wrong. A difference between real lotteries and prefaces is that a winning lottery ticket is generally an intended feature of the lottery, whereas incorrect facts are generally unintended.
Despite these similarities, Pollock gives a novel argument suggesting that the preface paradox warrants qualitatively different treatment from the lottery, using as a rationale the differences between real lotteries and prefaces. This draws a clear line between the work of Pollock and the work of Kyburg, both of whom have had a prominent influence in recent thinking on nonmonotonic reasoning in AI.
This note shows there are real lotteries with the formal structure of the preface paradox and possibly prefaces with the formal structure of lotteries. The surprising conclusion is that within Pollock's framework, the treatment of any problem with a formal structure resembling the lottery (or the preface) depends on the process by which winning tickets (or publishing errors) are generated. The rationales given by Pollock seem to be unrelated to the actual mechanisms implemented.     

相干命题逻辑系统R的一种演绎生成算法

本文提出了相干命题逻辑系统R的一种演绎生成算法--试探法。该算法采用后向推理法,依据推理规则将待证命题逐步分解成子命题并构造一棵证明树,对系统R中的定理证明取得了较好的效果。     

A Milestone Reached and a Secret Revealed

In this special issue of the Journal of Automated Reasoning, this article sets the stage for the succeeding articles, all of which focus on finding proofs of theorems of formal logic and on the various methodologies that were employed. The proofs that are offered mark an important milestone for automated reasoning and for logic, for each of them is indeed new. One key question this article answers is why an automated reasoning program was able to find proofs that had eluded some of the finest mathematicians and logicians for many, many decades.     

Computers in law — Some questions

The use of the computer in the legal arena has seen a rapid increase over the last decade ranging from the simple level where it is used to gain access to information to the complex level where it is used for diagnostic and decision making purposes. This second use of technology makes certain assumptions at the theoretical level regarding the nature of law and legal reasoning. This paper outlines in brief the jurisprudential assumptions made and the resulting questions raised as a consequence of the possiblity of ascribing legal functions to intelligent computer systems.     

AN ARGUMENT-BASED APPROACH TO NONMONOTONIC REASONING*

We define an argument system to be a pair consisting of a set of inference rules and a set of completeness conditions. Inference rules are used to build arguments. Completeness conditions are used to define argument structures, which are sets of arguments supporting belief sets. We reformulate Reiter's default logic as special argument systems. This enables us, among other things, to apply the negation-as-failure rule to general default theories. We also speculate on some other potential uses of our argument systems.     

Computers and legal reasoning: Developments in Germany

The importance of reasoning in law is pointed out. Law and jurisprudence belong to the reasoning-conscious disciplines. Accordingly, there is a long tradition of logic in law. The specific methods of professional work in law are to be seen in close connection with legal reasoning. The advent of computers at first did not touch upon legal reasoning (or the professional work in law). At first computers could be used only for general auxiliary functions (e.g., numerical calculations in tax law). Gradually, the use of computers for auxiliary functions in law has become more specific and more sophisticated (e.g., legal information retrieval), touching more closely upon professional legal work. Moreover, renewed interest in AI has also fostered interest in AI in law, especially for legal expert systems. AI techniques can be used in support of legal reasoning. Yet until now legal expert systems have remained in the research and development stage and have hardly succeeded in becoming a profitable tool for the profession. Therefore it is hoped that the two lines of computer support, for auxiliary functions in law and for immediate support of legal reasoning, may unite in the future.Herbert Fiedler is professor of Legal Informatics, general theory of law and penal law in the Department of Economics and Law at the University of Bonn.     

在一类缺省理论中关于证明理论的完备性问题

缺省推理是各种非单调推理系统中最在影响的系统之一。Ｒ。Ｒｅｉｔｅｒ对规范缺省理论作了一系列的研究。他还提出了证明理论，并证明了这一证明理论对于规范缺省理论来说是完备的。Ｗ。Ｅｔｈｅｒｉｎｇｔｏｎ则提出了应用范围更为广泛的有序半规范缺省理论。本文先证明了这类缺省理论具有半单调性等各种性质，然后证明了Ｒ。Ｒｅｉｔｅｒ的证明理论对于有序半规范缺省理论也是完备的。     

The use of CAI to enhance human interaction in the learning of deductive proof construction

It is unfortunate that most forms of CAI either decrease or replace student-teacher interaction and rarely promote student-student interaction in a deliberate fashion. The project described here, however, aims at improving human interaction in a deductive logic course via the use of a proof-checking computer program. This program supports analyses of student performance which guide in-class instruction on a real-time basis. It is a widely held belief that individualization promotes effectiveness in teaching and that CAI promotes individualization. Some questions are raised about these beliefs, and the conclusion drawn is that the prospects for a computer technology that enhances rather than diminishes human interaction should be more vigorously explored. Ultimately, the efforts reported here are intended to show that the use of computers in education need not constitute a form of separating teachers from their students, but rather can provide information concerning student needs and can supply opportunities for addressing those needs both within and outside the classroom.Marvin Croy is an associate professor of philosophy at the University of North Carolina at Charlotte. His current interests are in developing CAI that improves both in-class instruction and the quality of teacher-student interaction while simultaneously integrating teaching with research. This work was supported in part by a Curriculum and Instructional Development Grant funded by the Foundation of the University of North Carolina at Charlotte and by the State of North Carolina. An earlier version of this paper was read at the Eighth International Conference on Computers and the Humanities held at the University of South Carolina, April, 1987     

基于实例的不确定检索模型的研究

传统的基于实例推理系统中的检索模型缺乏对不确定环境的适应性。为此采用证据理论方法构造一种不确定实例检索模型,从而可以有效地处理实例检索中的不确定性,并能提高基于实例推理系统的性能。     

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.