Discourse analysis for a Legal Expert System

Informatics for the Law: LEXIS—A legal expert system on Italian family law

A legal expert system expresses as a set of formal rules the norms found in the provisions of a statute or regulation, in case law or other legal texts. The process of constructing the system involves interpreting these legal texts and recasting each of them into one or more formal legal rules. The primary sources of law or law-formulations, to use Susskind’s term [Susskind 87, 36-37, 124], must be transformed into law-statements—statements about what the content of the law is—and these in turn must be translated into a formal language as rules of inference which Susskind terms legal productions. These transformations take place outside the context of specific cases, that is without reference to concrete legal problems those rules are designed to solve. The construction of a legal expert system involves two conceptual steps: to identify the legal norms that a statute conveys and to express these norms as formal rules. Several strategies have been proposed for this transformation process. Some consist of a rather straightforward transposition of law texts into formal language at the expense of a substantial loss of meaning of the legal concepts involved; others call for a subtler and more complex legal analysis. In all cases, however, what is at stake is the interpretation of legal documents. The problem of interpreting legal documents is well known to lawyers. In legal usage, the term interpretation is employed when the meaning of a legal text, typically a statutory provision, has to be assessed in a concrete situation. In constructing expert systems, one must interpret legal documents ahead of such concrete applications. This interpretation can only be provisional. The best one can do in constructing the knowledge base is to foreclose as few as possible of the meanings for particular provisions one may ultimately want to consider in concrete situations. Conversely, when using the system in a particular situation, one may want to consider different interpretations and their

Based on the interpretation on the evolution of theoretical basis of the construction of legal expert system as the clue, this article mainly analyzes and points out the dilemma faced by symbolism and connectionism as the algorithm on construction of legal expert system. Through defeasible reasoning, a contextual-based legal expert system could be realized. The legal expert system should be constructed with the judge as the center character, in which the personality of the judge could not necessarily be eliminated. As a result, the article provides a model of a legal expert system based on dual processing, including factual argumentation and legal argumentation.

This paper presents a critical analysis of a legal expert system architecture, focusing the knowledge representation that represents the most important step in the construction of a modern legal information system. After a long period of experience, we can speak of global systems, because the formalized system knowledge is only a part of system data that may be improved to the user also from a periferic data bases. The new legal systems are tools that can offer information for decision aid and user consulting from different modules and also they offer a sophisticated information retrieval founded, for instance, upon hypertext models or thesauri.

Since 1992, about 30 Japanese lawyers and computer scientists have been intensively engaged in a project of systematizing and computerizing legal reasoning. This project is the Study of Development of a Legal Expert System - Exploration of Legal Knowledge Structure and Implementation of Legal Reasoning or, in short, the "Legal Expert" Project. In this paper, I would like to introduce the Legal Expert project, explaining the goals, study organizations and their tasks in constructing legal expert systems in Japan.

Legal reasoning involves case analysis in statutory as well as real world perspectives. The impact of real world perspective on case analysis poses a serious challenge to knowledge engineers for building legal expert systems. A legal expert system intends to provide intelligent support to legal professionals. The proposed legal predictive system is an attempt to predict the most probable outcome of a case according to statutory as well as real world knowledge of the legal domain. The system accepts the current fact situation of a case and analyses it interactively with legal personnel. This work introduces a frame-like knowledge structure,lattice, with two-dimensional attributes. This paper contains a detailed discussion on artificial intelligence-based case analysis of theft cases in a real world perspective.

The Mission Operations Directorate (MOD) at the Johnson Space Center (JSC) is responsible for the safe operation and mission success of manned space flights. The MITRE Corporation, working with MOD, is developing requirements for the Operations Management System (OMS) to automate many aspects of flight control for the Space Station onboard systems. To help develop these requirements, the Integrated Status Assessment (ISA) expert system prototype was built to perform Station-wide failure diagnosis. This paper describes the OMS, how the ISA prototype was built, and how the prototype is being used to help define the OMS.Currently the Space Shuttle is managed on the ground using a hierarchy of control personnel. A flight director responsible for the overall Shuttle mission, a number of front room flight controllers are each responsible for a different system, and many back room controllers support various front room controllers. This system has been used since the early days of space flight and is very manpower intensive. A similar hierarchy is seen in an automated system for the Space Station. The back room controllers can be augmented with smart components and sensors on the Station and the front room controllers can have their jobs aided with expert systems. At the highest level is the OMS which works at the flight director level getting summary information from the various systems in the Station.The OMS will include onboard automation, ground based automation, onboard manual operations, and ground based operations. One of the functions of the OMS is to perform a Station-wide status assessment and failure diagnosis of the Station. This Station-wide view is very important because all of the systems interact with each other and a failure in one system will have impacts on the other systems.It became evident early in discussion with to the MOD flight controllers that prototypes would be very helpful in the process of gathering requirements for the OMS. The prototypes were used to gather additional requirements, to expose people to new ideas and technologies, and study the feasibility of these technologies for systems management.Because the task of assessing the status of space vehicles is a complex job that requires “expert” knowledge to find heuristic solutions to problems, an expert system approach was chosen to prototype the ISA system. The initial domain of the expert system was the KU band portion of the communications and tracking system (one of the onboard “core” Space Station Systems).The ISA prototype expert system consists of a knowledge base, an inference engine, and a user interface. The ISA system was designed as a hybrid expert system using different methodologies: object-oriented programming, rule-based programming using both shallow and deep reasoning, and qualitative modeling.The ISA prototype has been very successful in its goals. ISA has demonstrated new technology and ideas to the NASA operations community, helped define requirements for the OMS, and shown the feasibility of using hierarchical expert systems to monitor complex systems. The ISA prototype, along with other OMS prototypes, are being integrated in a test bed environment with other space station prototypes to form the Space Station Information System (SSIS) End-to-end Test Capability (ETC) which will have components all over the world. The results of the ETC will influence the Space Station design and be a test environment for software and hardware for years to come.

Kamp's Discourse Representation Theory is a major breakthrough regarding the systematic translation of natural language discourse into logical form. We have therefore chosen to marry the User Specialty Languages System, which was originally designed as a natural language frontend to a relational database system, with this new theory. In the paper we try to show taking - for the sake of simplicity - Kamp's fragment of English how this is achieved. The research reported is going on in the context of the project Linguistics and Logic Based Legal Expert System undertaken jointly by the IBM Heidelberg Scientific Center and the Universitat Tubingen.

Application of goal tree-success tree model as the knowledge-base of operator advisory systems

Knowledge representation has been idenfied as the most important issue facing the field of AI and Law.1 The nature of legal reasoning and decision making, in particular the way judges decide hard cases, have been important jurisprudential issues for many years. it is inescapable that a Iegaf expert system which attempts to emulate the reasoning processes of a lawyer must embody a theory of legaf reasotting.2 Building a legal expert system is thus not just an exercise in computer programming, but requires sotid and articulated jurisprudentiaf foundations.

Negaid is posed as a plugin of a legal expert system shell, eGanges, which provides negotiation support for conflict prevention applications. A cohabitation contract application that uses an ontology of potential conflict demonstrates the negotiation logic of the expert system as seamless with the Negaid algorithm, a revised version of the Family Winner algorithm. The new negotiation algorithm incorporates the use and reuse of the cohabitation contract application until a list of differences can be identified for resolution as a matter of compromise. The list is then subjected to the Negaid algorithm, which assists in the negotiation process by suggesting trade-offs.
\nICAIL 2007 June 4 – June 8, 2007 Stanford University 
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SUNNARY The SeismicDeconvolution Advisor (SDA) is designed to aid the user in thk understanding of deconvolution concepts and in the determination of processing parameters for predictive deconvolution. Fundamental deconvolution concepts, predictive deconvolution parameters, examples, and graphic helps are included in the system. The Seismic Deconvolution Advisor, unlike batch-job systems or other interactive systems, provides help to guide the user in the understanding and application of the deconvolution process. Predictive Deconvolution Module (PDM), a branch of SDA, determines the parameters for prestack predictive deconvolution tests. Discussions with five experts, a deconvolution processing class, practical experience, and reading material provided knowledge for the expert system. The rule-based, expert system software shell, PERSONAL CONSULTANTTM PLUS (Texas Instruments, 1986), was used with the backward-chaining option. The prototype expert system contains 280 rules, 377 parameters, and 36 graphics, and requires half megabyte of space on an IBM microcomputer. The user is expected to have a nominal knowledge of seismic data processing. The major strength of the SDA system is that this system gives advice and guidance to the user concerning the preconditioning, predictive-deconvolution parameters and postconditioning of seismic data. Weaknesses are that it has a limited knowledge base, and no deconvolution processing is available within SDA. Limited testing has been performed on the system periodically by the expert, advisor, and a committee member. Suggestions were provided to address possible errors in input/output characteristics, inference rules, control strategies, and text examples. The SDA has been shown to reach satisfactory decisions in its domain of expertise.

ABSTRACTThe assessment of the current market value of residential property is a potential source of anxiety for the typical homeowner. Common criticisms of the existing appraisal process include excessive subjectivity and inconsistency across properties and through time. This paper examines the nature of decision support required for valuation decisions and the appropriateness of applying expert system technologies to evaluate the recoverable value of the single‐family residence. The expert system approach allows for the integration of the qualitative and quantitative aspects of appraisal, while introducing the beneficial dimensions of increased objectivity, comprehensiveness, and consistency. A prototype expert system is offered that enables the end user to conduct a market analysis of a subject property. Unlike most expert system applications that seek a diagnostic or classification response, this study explores a numerical intent for the system, in a decision‐making environment that is traditionally viewed as highly judgmental. The system's early validation results show promise of proving effective as such an evaluation aid.

In our continuing effort to incorporate state-of-the-art technologies into our services, Fluor Daniel evaluated some of its engineering activities to determine which ones will benefit the most from Expert Systems (ES) technology. Prototype Expert Systems were developed for selected activities such as conceptual cost estimating, project scheduling, hazard analysis, process control, etc. The objective of prototyping was not only to provide proof of concept, but also to identify a suitable expert system shell which would enable cost-effective Expert System development. Our experience demonstrates that an Expert System shell based on object-oriented knowledge representation is more suitable for some engineering applications than a purely rule-based system. We also found that the general purpose tools we used do not have the graphical capability necessary for some engineering applications and that the DBase interface and reporting capability need improvement.

Validating expert system prototypes using the turing test