Reasoning with Rules and Precedents A Computational Model of Legal Analysis

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...

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Bibliographic Details
Main Author: Branting, L. Karl
Format: eBook
Language:English
Published: Dordrecht Springer Netherlands 2000, 2000
Edition:1st ed. 2000
Subjects:
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
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245 0 0 |a Reasoning with Rules and Precedents  |h Elektronische Ressource  |b A Computational Model of Legal Analysis  |c by L. Karl Branting 
250 |a 1st ed. 2000 
260 |a Dordrecht  |b Springer Netherlands  |c 2000, 2000 
300 |a XIII, 219 p  |b online resource 
505 0 |a 1. Introduction -- 2. A Framework for Integrating Rules and Exemplars -- 3. A Formal Model of Ratio Decidendi -- 4. Grebe: Integrating Rules and Precedents for Legal Analysis -- 5. Examples of GREBE’s Legal Analysis -- 6. Evaluation -- 7. Related Work -- 8. Research Contributions -- References -- Appendices -- A—GREBE’s Analysis of 7 Worker’s Compensation Hypotheticals -- B—Legal Precedents in the Worker’s Compensation Knowledge Base -- C—Predicates Having Precedents as Warrants -- D—21 Hypothetical Cases -- E—GREBE’s Relation Vocabulary -- F—GREBE’s Structure Matching Algorithm 
653 |a Law / History 
653 |a Artificial Intelligence 
653 |a Philosophy of Law 
653 |a Theories of Law, Philosophy of Law, Legal History 
653 |a Artificial intelligence 
653 |a Law / Philosophy 
041 0 7 |a eng  |2 ISO 639-2 
989 |b SBA  |a Springer Book Archives -2004 
028 5 0 |a 10.1007/978-94-017-2848-5 
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520 |a 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