Legal Reasoning Models

Abstract

Research in legal reasoning models investigates formal and computational theories of how legal experts analyze problems, create arguments, and make decisions. Rule-based legal expert systems using logical inference techniques have been developed and used successfully in a number of legal domains, especially those dominated by complex regulations such as taxation and social benefits administration. However, it is the view of most researchers that the essence of legal reasoning is its open-textured and indeterminate nature. Two essential cognitive abilities for legal reasoning models include: case-based reasoning, the use of legal precedents to interpret open-textured or conflicting rules and concepts; and adversarial reasoning, the ability to create persuasive arguments for both sides of an issue. Models of legal case-based reasoning confront several problems: representation of cases; organization of and retrieval from a case database; similarity ranking of retrieved prior cases relative to a new case; and creation of case-based legal arguments. Models of legal argumentation fall into three broad categories: case-based, logic-based, and legal discourse models. Promising new directions for research in legal reasoning include formal legal ontologies and the use of legal models in electronic commerce.