Representing teleological structure in case-based legal reasoning: the missing link
ICAIL '93 Proceedings of the 4th international conference on Artificial intelligence and law
Teaching case-based argumentation through a model and examples
Teaching case-based argumentation through a model and examples
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Law, learning and representation
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A reduction-graph model of precedent in legal analysis
Artificial Intelligence - Special issue on AI and law
A model of legal reasoning with cases incorporating theories and values
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Artificial Intelligence - Special issue on AI and law
Artificial argument assistants for defeasible argumentation
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Towards a computational account of persuasion in law
ICAIL '03 Proceedings of the 9th international conference on Artificial intelligence and law
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ICAIL '03 Proceedings of the 9th international conference on Artificial intelligence and law
A meta-level approach to the analysis of legal phenomena based on the key concept of reduction
ICAIL '03 Proceedings of the 9th international conference on Artificial intelligence and law
Predicting outcomes of case based legal arguments
ICAIL '03 Proceedings of the 9th international conference on Artificial intelligence and law
Try to see it my way: modelling persuasion in legal discourse
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Additive consolidation for dialogue game
ICAIL '05 Proceedings of the 10th international conference on Artificial intelligence and law
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Dialogue game tree with nondeterministic additive consolidation
CLIMA VII'06 Proceedings of the 7th international conference on Computational logic in multi-agent systems
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In this paper we put forward a formal description of theories which can be used to record understanding of, and explain decisions in, case law domains. We believe that reasoning with cases involves all of theory construction, use and evaluation, and that awareness of the theory which provides a context for case based arguments is essential to understanding such arguments. Moreover, our account of these theories includes a systematic link between factors and values, which we believe is necessary to explain why some arguments prove to be more persuasive than others. We begin by formalising the various elements that the theories contain, and then provide a set of theory constructors which allow theories to built up from the background of decided cases. We show how such theories can be used to explain decisions on particular cases. We discuss how theories can be compared and evaluated. We then show how the argument moves of HYPO and CATO can be understood in terms of our framework. We conclude with a brief discussion of an implementation of the framework, and a summary of the major features of our approach.