. This article surveys the use of logic in computational models of legal reasoning, against the background of a four-layered view on legal argument. This view comprises a logical layer (constructing an argument) ; a dialectical layer (comparing and assessing conicting arguments) ; a procedural layer (regulating the process of argumentation); and a strategic, or heuristic layer (arguing persuasively). Each further layer presupposes, and is built around the previous layers. At the rst two layers the information base is xed, while at the third and fourth layer it is constructed dynamically, during a dialogue or dispute. 1

te EULE2 checks whether the knowledge base is still valid with respect to the underlying regulations and federal law. If a violation occurs, EULE2 would reject the modification and offer an explanation to the office worker about the violation. Has a knowledge base manipulation proved valid, EULE2 checks for each action that leads from the current state to a subsequent state whether it is now executable or not. Certain actions may be illegal, certain others possible, while still others are obligatory. The office worker may decide to initiate one of the possible actions, may inquire why an 1 EULE2 is the knowledge-based version of a hypertext-based information system called EULE. obligatory action must be executed, or may ask why an illegal action is not permitted. Finally, the office worker selects an action for execution. The action causes new instances to be created or existing instances to be modified and leads to a new state. To achieve the functiona

We propose a software architecture for user-cooperative systems, like knowledge systems. This architecture incorporates important notions for building up a context, such as cooperation, explanations and incremental knowledge acquisition. Our main concern in this paper is representation methodology. We show that the architecture can be realized as a pure first order theory, which we argue constitutes a good basis for system development. A declarative relational language promotes modularity, clarity and maintainability. The system we outline is implemented in logic programming.

We are researching the problem of open texture in legal reasoning and how it leads to the evolution of legal ontologies. Concepts in law are open-textured, they can’t be uniquely matched to common sense concepts which describe real-world events. The argumentation that occurs in many legal cases is about the meaning of legal concepts. These legal concepts evolve through this argumentation. Our aim is to build computational models of this legal reasoning. We argue for the importance of ontologies for meta-knowledge in modelling this argumentation. We also argue that this work has relevance for ontology matching. 1 Legal Reasoning and Open Texture Legal reasoning is not simply a matter of identifying the subsumptions between legal concepts and real-world concepts. Legal concepts are not precisely defined enough for this: the relationship between them and the real-world is not exact. H.L.A. Hart, who was the first

the date of receipt and acceptance should be inserted later Abstract This paper studies the use of hypothetical and value-based reasoning in US Supreme-Court cases concerning the United States Fourth Amendment. Drawing upon formal AI & Law models of legal argument a semi-formal reconstruction is given of parts of the Carney case, which has been studied previously in AI & law research on case-based reasoning. As part of the reconstruction, a semi-formal proposal is made for extending the formal AI & Law models with forms of metalevel reasoning in several argument schemes. The result is compared with Rissland’s (1989) analysis in terms of dimensions and Ashley’s (2008) analysis in terms of his process model of legal argument with hypotheticals. 1