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The simulation of inference processes performed by lawyers can be seen as one way to create advisory legal system. In order to simulate such a process as accurately as possible, it is indispensable to make a clear-cut distinction between the provision itself, and its interpretation and inference mechanisms. This distinction would allow for preserving both the universal character of the provision and its applicability to various legal problems. The author’s main objective was to model a selected legal act, together with the inference rules applied, and to represent them in an advisory system, focusing on the most accurate representation of both the content and inference rules. Given that the laws which stand in contradiction prove to be the major challenge, they will constitute the primary focus of this study.
Słowa kluczowe
Rocznik
Tom
Strony
129--145
Opis fizyczny
Bibliogr. 30 poz.
Twórcy
autor
- Intitute of Computer Science Maria Curie-Sklodowska University, pl. Marii Curie-Sklodowskiej 1. Lublin
Bibliografia
- [1] Agricultural tax act. http://prawo-nieruchomosci.krn.pl/Ustawa-o-podatkurolnym- 1 2 36.html (2010)
- [2] Bench-Capon, T., Sartor, G.: Theory based explanation of case law domains:. In: ICAIL ’01: Proceedings of the 4th international conference on Artificial intelligence and law, pp. 12-21. ACM, New York, NY, USA (2001)
- [3] Borsari, G., Cevenini, C., Contissa, G., Morini, S., Sartor, G., Still, P.: Hare: an italian application of softlaw’s statute expert technology. In: ICAIL ’05: Proceedings of the 10th international conference on Artificial Intelligence and Law, pp. 225-229. ACM, New York, NY, USA (2005)
- [4] Gordon, T.: Some problems with prolog as a knowledge representation language for legal expert system. International Review of Law, Computers and Technology 3, 52-67 (1987)
- [5] Gordon, T.: Constructing arguments with a computational model of an argumentation scheme for legal rules: Interpreting legal rules as reasoning policies. In: Proceedings of the 11th International Conference on Artificial Intelligence and Law, pp. 117-121. ACM, New York, NY, USA (2007)
- [6] Hage, J.: Law and defeasibility. Artificial Intelligence and Law 11, 221-243 (2003)
- [7] Hage, J.: Studies in Legal Logic. Springer (2005)
- [8] Horty, J.: Argument construction and reinstatement in logics for defeasible reasoning. Artificial Intelligence and Law 9, 1-28 (2001)
- [9] Horty, J.F.: Nonmonotonic techniques in the formalisation of commonsense normative reasoning. Proceedings Workshop on Nonmonotonic Reasoning pp. 74-84 (1993)
- [10] Kowalski, R., Toni, F.: Abstract argumentation. Articial Intelligence and Law 4, 275-296 (1996)
- [11] MacDermott, D.: Non-monotonic ii- non-monotonic modal theories. Journal of ACM 29(1), 33-57 (1982)
- [12] Mccarthy: Circumscription a form of non-monotonic reasoning. Artificial Intelligence 13, 27-39 (1980)
- [13] Nute, D.: Defeasible logic. In: INAP’01: Proceedings of the Applications of prolog 14th international conference on Web knowledge management and decision support, pp. 151-169. Springer-Verlag, Berlin, Heidelberg (2003)
- [14] Oskamp, A.: Model for knowledge and legal expert systems. Artificial Intelligence and Law 1, 245-274 (1992)
- [15] Prakken, H.: Two approaches to the formalisation of defeasible deontic reasoning. Studia Logica pp. 73-90 (1996)
- [16] Prakken, H.: Coherence and flexibility in dialogue games for argumentation. Journal of logic and computation 15, 1009-1040 (2005)
- [17] Prakken, H.: Formalising ordinary legal disputes: a case study. Artificial Intelligence and Law 16, 333-359 (2008)
- [18] Prakken, H., Sartor, G.: A system for defeasible argumentation, with defeasible priorities, Lecture Notes in Computer Science, vol. 1085, pp. 510-524. Springer Berlin / Heidelberg (1996)
- [19] Prakken, H., Sartor, G.: Argument-based extended logic programming with defeasible priorities. Journal of Applied Non-classical Logics 7(1) (1997)
- [20] Prakken, H., Sartor, G.: The three faces of defeasibility in the law. Ratio Juris 17(1), 118-139 (2004)
- [21] Prakken, H., Sartor, G.: Formalising arguments about the burden of persuasion. In: ICAIL ’07: Proceedings of the 11th international conference on Artificial intelligence and law, pp. 97-106. ACM, New York, NY, USA (2007)
- [22] Reiter, R.: A logic for default reasoning. Artificial Intelligence 13, 81-132 (1980)
- [23] Sartor, G.: The structure of norm conditions and nonmonotonic reasoning in law. In: ICAIL ’91: Proceedings of the 3rd International Conference on Artificial intelligence and law, pp. 155-164 (1991)
- [24] Sartor, G.: Normative conflicts in legal reasoning. Artificial Intelligence and Law 1, 209-235 (1992)
- [25] Sartor, G.: A simple computational model for nonmonotonic and adversarial legal reasoning. In: ICAIL ’93: Proceedings of the 4th international conference on Artificial intelligence and law, pp. 192-201 (1993)
- [26] Sergot M, J., Sadri, F., Kowalski R, A., Kriwaczek, F., Hammond, P., Cory H, T.: The british nationality act as a logic program. Communications of the ACM 29(5), 370-386 (1986). DOI http://doi.acm.org/10.1145/5689.5920
- [27] Sherman, D.: A prolog model of the income tax act of canada. In: ICAIL ’87: Proceedings of the 1st international conference on Artificial intelligence and law, pp. 127-136 (1987)
- [28] Van Der Torre L W, N., Yao-Huata, N.: Defeasible Deontic Logic, chap. The Many Faces Of Defeasibility In Defeasible Deontic Logic, pp. 79-122. Kluwer (1997)
- [29] Walton, D.: Fundamentals of Critical Argumentation. Cambridge University Press (2006)
- [30] Zurek, T., Kruk, E.: Supporting of legal reasoning for cases which are not strictly regulated by law. In: ICAIL ’09: Proceedings of the 12th International Conference on Artificial Intelligence and Law, pp. 220-221 (2009)
Typ dokumentu
Bibliografia
Identyfikator YADDA
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