Download Free Modelling Legal Argument Book in PDF and EPUB Free Download. You can read online Modelling Legal Argument and write the review.

"Modeling Legal Argument "provides a comprehensive treatment of case-based reasoning and a detailed description of a computer program called Hypo, that models the way attorneys argue with cases, real and hypothetical. The program offers significant advantages over "keyword" case retrieval systems in the legal field and demonstrates how to design expert systems that assist the user by presenting reasonable alternative answers on all sides of an issue and by citing case examples to explain their advice.Hypo analyzes problem situations dealing with trade secrets disputes, retrieves relevant legal cases from its database and fashions them into reasonable legal arguments about who should win. The arguments demonstrate the program's ability to reason symbolically with past cases, to draw factual analogies between cases, to cite them in arguments, to distinguish them, and to pose counter-examples and hypotheticals based on past cases."Modeling Legal Argument "discusses the law as a paradigm of case-based argument, introduces Hypo and its adversarial reasoning process, provides an overview of the Hypo program, and gives extended examples of the model's reasoning capabilities. It describes the case knowledge base, a dimensional index, basic mechanisms of case-based reasoning, and offers a theory of case-based argument in Hypo. Ashley evaluates Hypo's performance and takes up adversarial case-based reasoning beyond the law and extensions of the Hypo model.Kevin D. Ashley is a Research Scientist at the Learning Research an Development Center and Assistant Professor of Law at the University of Pittsburgh. "Modeling Legal Argument is "included in the Artificial Intelligence and Legal Reasoning series, edited by L. Thorne McCarty and Edwina L. Rissland.
This book is a revised and extended version of my PhD Thesis 'Logical Tools for Modelling Legal Argument', which I defended on 14 January 1993 at the Free University Amsterdam. The first five chapters of the thesis have remained almost completely unchanged but the other chapters have undergone considerable revision and expansion. Most importantly, I have replaced the formal argument-based system of the old Chapters 6, 7 and 8 with a revised and extended system, whieh I have developed during the last three years in collaboration with Giovanni Sartor. Apart from some technical improvements, the main additions to the old system are the enriehment of its language with a nonprovability operator, and the ability to formalise reasoning about preference criteria. Moreover, the new system has a very intuitive dialectieal form, as opposed to the rather unintuitive fixed-point appearance of the old system. Another important revision is the split of the old Chapter 9 into two new chapters. The old Section 9. 1 on related research has been updated and expanded into a whole chapter, while the rest of the old chapter is now in revised form in Chapter 10. This chapter also contains two new contributions, a detailed discussion of Gordon's Pleadings Game, and a general description of a multi-Iayered overall view on the structure of argu mentation, comprising a logieal, dialectical, procedural and strategie layer. Finally, in the revised conclusion I have paid more attention to the relevance of my investigations for legal philosophy and argumentation theory.
The investigation of computational models of argument is a rich and fascinating interdisciplinary research field with two ultimate aims: the theoretical goal of understanding argumentation as a cognitive phenomenon by modeling it in computer programs, and the practical goal of supporting the development of computer-based systems able to engage in argumentation-related activities with human users or among themselves. The biennial International Conferences on Computational Models of Argument (COMMA) provide a dedicated forum for the presentation and discussion of the latest advancements in the field, and cover both basic research and innovative applications. This book presents the proceedings of COMMA 2020. Due to the Covid-19 pandemic, COMMA 2020 was held as an online event on the originally scheduled dates of 8 -11 September 2020, organised by the University of Perugia, Italy. The book includes 28 full papers and 13 short papers selected from a total of 78 submissions, the abstracts of 3 invited talks and 13 demonstration abstracts. The interdisciplinary nature of the field is reflected, and contributions cover both theory and practice. Theoretical contributions include new formal models, the study of formal or computational properties of models, designs for implemented systems and experimental research. Practical papers include applications to medicine, law and criminal investigation, chatbots and online product reviews. The argument-mining trend from previous COMMA’s is continued, while an emerging trend this year is the use of argumentation for explainable AI. The book provided an overview of the latest work on computational models of argument, and will be of interest to all those working in the field.
This book describes how text analytics and computational models of legal reasoning will improve legal IR and let computers help humans solve legal problems.
After years of teaching law courses to undergraduate, graduate, and law students, Michael Evan Gold has come to believe that the traditional way of teaching – analysis, explanation, and example – is superior to the Socratic Method for students at the outset of their studies. In courses taught Socratically, even the most gifted students can struggle, and many others are lost in a fog for months. Gold offers a meta approach to teaching legal reasoning, bringing the process of argumentation to the fore. Using examples both from the law and from daily life, Gold's book will help undergraduates and first-year law students to understand legal discourse. The book analyzes and illustrates the principles of legal reasoning, such as logical deduction, analogies and distinctions, and application of law to fact, and even solves the mystery of how to spot an issue. In Gold's experience, students who understand the principles of analytical thinking are able to understand arguments, to evaluate and reply to them, and ultimately to construct sound arguments of their own.
In the study of forms of legal reasoning logic and argumentation theory long followed separate tracks. Recently, however, developments in Artificial Intelligence and Law have paved the way for overcoming this separation. Logic has widened its scope to defeasible argumentation, and informal accounts of analogy and dialectics have inspired the construction of computer programs. Thus the prospect is emerging of an integrated logical and dialectical account of legal argument, adding to the understanding of legal reasoning, and providing a formal basis for computer tools that assist and mediate legal debates while leaving room for human initiative.
Few areas of human expertise are so well understood that they can be completely reduced to general principles. Similarly, there are few domains in which experience is so extensive that every new problem precisely matches a previous problem whose solution is known. When neither rules nor examples are individually sufficient, problem-solving expertise depends on integrating both. This book presents a computational framework for the integration of rules and cases for analytic tasks typified by legal analysis. The book uses the framework for integrating cases and rules as a basis for a new model of legal precedents. This model explains how the theory under which a case is decided controls the case's precedential effect. The framework for integrating rules and cases is implemented in GREBE, a system for legal analysis. The book presents techniques for representing, indexing, and comparing complex cases and for converting justification structures based on rules and case into natural-language text. This book will interest researchers in artificial intelligence, particularly those involved in case-based reasoning, artificial intelligence and law, and formal models of argumentation, and to scholars in legal philosophy, jurisprudence, and analogical reasoning.
In The Uses of Argument (1958), Stephen Toulmin proposed a model for the layout of arguments: claim, data, warrant, qualifier, rebuttal, backing. Since then, Toulmin’s model has been appropriated, adapted and extended by researchers in speech communications, philosophy and artificial intelligence. This book assembles the best contemporary reflection in these fields, extending or challenging Toulmin’s ideas in ways that make fresh contributions to the theory of analysing and evaluating arguments.
The International Court of Justice at The Hague is the principal judicial organ of the UN, and the successor of the Permanent Court of International Justice (1923–1946), which was the first real permanent court of justice at the international level. This 2005 book analyses the groundbreaking contribution of the Permanent Court to international law, both in terms of judicial technique and the development of legal principle. The book draws on archival material left by judges and other persons involved in the work of the Permanent Court, giving fascinating insights into many of its most important decisions and the individuals who made them (Huber, Anzilotti, Moore, Hammerskjöld and others). At the same time it examines international legal argument in the Permanent Court, basing its approach on a developed model of international legal argument that stresses the intimate relationships between international and national lawyers and between international and national law.
The judiciary is in the early stages of a transformation in which AI (Artificial Intelligence) technology will help to make the judicial process faster, cheaper, and more predictable without compromising the integrity of judges' discretionary reasoning. Judicial decision-making is an area of daunting complexity, where highly sophisticated legal expertise merges with cognitive and emotional competence. How can AI contribute to a process that encompasses such a wide range of knowledge, judgment, and experience? Rather than aiming at the impossible dream (or nightmare) of building an automatic judge, AI research has had two more practical goals: producing tools to support judicial activities, including programs for intelligent document assembly, case retrieval, and support for discretionary decision-making; and developing new analytical tools for understanding and modeling the judicial process, such as case-based reasoning and formal models of dialectics, argumentation, and negotiation. Judges, squeezed between tightening budgets and increasing demands for justice, are desperately trying to maintain the quality of their decision-making process while coping with time and resource limitations. Flexible AI tools for decision support may promote uniformity and efficiency in judicial practice, while supporting rational judicial discretion. Similarly, AI may promote flexibility, efficiency and accuracy in other judicial tasks, such as drafting various judicial documents. The contributions in this volume exemplify some of the directions that the AI transformation of the judiciary will take.