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  1.  30
    Defeasible reasoning in japanese criminal jurisprudence.Katsumi Nitta & Masato Shibasaki - 1997 - Artificial Intelligence and Law 5 (1-2):139-159.
    Modeling legal argumentation is one of the most important research in AI and Law, and a lot of models have been proposed. However, most research has not treated value judgement and debate. In this paper, we introduce a legal reasoning model which covers various aspects of legalreasoning such as making argument, selecting argument and debate.Furthermore, we present how criminal law is described and reasoned inthis model.
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  2.  23
    First international workshop on juris-informatics.Katsumi Nitta, Ken Satoh & Satoshi Tojo - 2008 - In Satoh (ed.), New Frontiers in Artificial Intelligence. Springer. pp. 347--348.
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  3.  13
    Overview of JURISIN 2008.Katsumi Nitta, Ken Satoh & Satoshi Tojo - 2009 - In Hattori (ed.), New Frontiers in Artificial Intelligence. Springer. pp. 211--212.
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  4.  13
    Computing argumentation semantics in answer set programming.Toshiko Wakaki & Katsumi Nitta - 2009 - In Hattori (ed.), New Frontiers in Artificial Intelligence. Springer. pp. 254--269.
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  5.  41
    Similarity of legal cases: From temporal relations of affairs. [REVIEW]Satoshi Tojo & Katsumi Nitta - 1997 - Artificial Intelligence and Law 5 (1-2):161-176.
    Case-based reasoning has played an important role in legal reasoning systems. As one criteria for similarity of cases, temporal relationsamong affairs in legal cases should be compared. Thus far in many legalreasoning systems, cases have been described as sequences of pointwiseevents, or at best, simple time intervals, and they have been related bypredicates such as before, after, while,and so on. However, such relations may depend on each implementer'spersonal view, and also require much labor to write down by hand. In this (...)
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