Induction of defeasible logic theories in the legal domain

Proceedings of the International Conference on Artificial Intelligence and Law

Volumn , Issue , 2003, Pages 204-213

  Johnston, Benjamin ^a   Governatori, Guido ^a  

^a UNIVERSITY OF QUEENSLAND   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATE SOLUTION; DEFEASIBLE LOGIC; LEGAL DOMAINS; LEGAL KNOWLEDGE; POTENTIAL BENEFITS; PRACTICAL ALGORITHMS;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; DECISION SUPPORT SYSTEMS; DECISION THEORY;

KNOWLEDGE REPRESENTATION;

EID: 33746891106     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1047788.1047834     Document Type: Conference Paper

References (36)

1. Rakesh Agrawal and Ramakrishnan Srikant. Fast algorithms for mining association rules. In Michael Stonebraker and Joseph Hellerstein, editors, Readings in Database Systems, chapter 7, pages 580-592. Morgan Kaufmann Publishers, 3rd edition, 1998.
2. Grigoris Antoniou, David Billington, Guido Governatori, and Michael Maher. On the modelling and analysis of regulations. In Proceedings of the 10th Australasian Conference on Information Systems, pages 20-29, 1999.
3. Grigoris Antoniou, David Billington, Guido Governatori, and Michael Maher. A flexible framework for defeasible logics. In AAAI/IAAI, pages 405-410, 2000.
4. Grigoris Antoniou, David Billington, Guido Governatori, and Michael Maher. Representation results for defeasible logic. ACM Transactions on Computational Logic, 2(2):255-287, April 2001.
5. Grigoris Antoniou, David Billington, Guido Governatori, Michael Maher, and Andrew Rock. A family of defeasible reasoning logics and its implementation. In Proceedings of the 14th European Conference on Artificial Intelligence, Amsterdam, 2000. IOS Press.
6. Grigoris Antoniou, David Billington, and Michael J. Maher. The analysis of regulations using defeasible rules. In Proceedings of the 32nd Hawaii International Conference on Systems Science. IEEE Press, 1999.
7. Grigoris Antoniou, Michael Maher, and David Billington. Defeasible logic versus logic programming without negation as failure. Journal of Logic Programming, 42(1):47-57, January 2000.
8. Giorgio Ausiello, Pierluigi Crescenzi, Giorgio Gambosi, Viggio Kann, Alberto Marchetti-Spaccamela, and Marco Protasi. Complexity and Approximation: Combinatorial Optimization Problems and their Approximability Properties, chapter Appendix B, page 426. Springer-Verlag, 1999. See also http://www.nada.kth.se/ viggo/problemlist/.
9. John Avery, Andrew Stranieri, Guido Governatori, and John Zeleznikow. The identification of defeasible rule sets from databases using association rules. Technical Report, University of Ballarat.
10. Trevor Bench-Capon. Neural networks and open texture. In Proceedings of the Fourth International Conference on Artificial Intelligence and Law. ACM Press, 1993.
11. Trevor Bench-Capon, Frans Coenen, and Paul Leng. An experiment in discovering association rules in the legal domain. In Proceedings of the Eleventh International Workshop on Database and Expert Systems Applications, pages 1056-1060, Los Alamitos, California, 2000. IEEE Computer Society.
12. David Billington. Defeasible logic is stable. Journal of Logic and Computation, 3:370-400, 1993.
13. Stefanie Bruninghaus and Kevin Ashley. Toward adding knowledge to learning algorithms for indexing legal cases. In The Seventh International Conference on Artificial Intelligence and Law, pages 9-17, 1999.
14. Michael Covington. Logical control of an elevator with defeasible logic. IEEE Transactions on Automatic Control, 45(7):1347-1349, 2000.
15. Beatrice Duval and Pascal Nicolas. Learning default theories. In Anthony Hunter and Simon Parsons, editors, ECSQARU, number 1638 in LNCS, pages 148-159, London, 1999. Springer.
16. Michael Garey and David Johnson. Computers and Intractability: A Guide to the Theory of NP-Completeness, chapter Appendix A, page 222. W. H. Freeman and Company, 1979.
17. Matthew Ginsberg. AI and nonmonotonic reasoning. In Dov Gabbay, Christopher Hogger, and John Robinson, editors, Handbook of Logic in Artificial Intelligence and Logic Programming, Volume 3. Oxford University Press, 1993.
18. Guido Governatori, Marlon Dumas, Arthur H. M. ter Hofstede, and Phillipa Oaks. A formal approach to protocols and strategies for (legal) negotiation. In Henry Prakken, editor, Procedings of the 8th International Conference on Artificial Intelligence and Law, pages 168-177. IAAIL, ACM Press, 2001.
19. Guido Governatori and Andrew Stranieri. Towards the application of association rules for defeasible rule discovery. In Bart Verheij, Arno Lodder, Ronald Loui, and Antoinette Muntjewerff, editors, Frontiers in Artificial Intelligence and Applications, volume 70. IOS Press, 2001. Proceedings of JURIX 2001.
20. Guido Governatori, Arthur H. M. ter Hofstede, and Phillipa Oaks. Defeasible logic for automated negotiation. In P. Swatman and P. M. Swatman, editors, Proceedings of CollECTeR. Deakin University, 2000.
21. Benjamin N. Grosof, Yannis Labrou, and Hoi Y. Chan. A declarative approach to business rules in contracts: courteous logic programs in xml. In Proceedings of the first ACM conference on Electronic commerce, pages 68-77. ACM Press, 1999.
22. Jaiwei Han, Jian Pei, and Yiwen Yin. Mining frequent patterns without candidate generation. In Weidong Chen, Jeffrey Naughton, and Philip Bernstein, editors, 2000 ACM-SIGMOD International Conference on Management of Data, pages 1-12, Dallas, Texas, 05 2000. ACM Press.
23. Katsumi Inoue and Yoshimitsu Kudoh. Learning extended logic programs. In Proceedings of the fifteenth International Joint Conference on Artificial Intelligence, Volume 1, pages 176-181. Morgan Kaufmann, 1997.
24. Benjamin Johnson and Guido Goverantori. An algorithm for the induction of defeasible logic theories from databases. In Klaus-Dieter Schewe and Xiaofang Zhou, editors, Database Technology 2003, number 17 in Conference Research and Practice of Information Technology, pages 75-83. Australian Computer Science Association, ACS, 4-7 February 2003.
25. Nada Lavrac and Sazo Dzeroski. Inductive Logic Programming: Techniques and Applications. Ellis Horwood, New York, 1994.
26. Michael Maher. Propositional defeasible logic has linear complexity. Theory and Practice of Logic Programming, 1(6):691-711, November 2001.
27. Pascal Nicolas and Beatrice Duval. Representation of incomplete knowledge by induction of default theories. In Thomas Eiter, Wolfgang Faber, and Miroslaw Truszczyr.ski, editors, Logic Programming and Nonmonotonic Reasoning, number 2173 in LNAI, pages 160-172. Springer, 2001.
28. Donald Nute. Defeasible logic. In Dov Gabbay, Christopher Hogger, and John Robinson, editors, Handbook of Logic in Artificial Intelligence and Logic Programming, volume 3. Oxford University Press, 1993.
29. Henry Praken. Logical Tools for Modelling Legal Argument. Kluwer Academic Publishers, 1997.
30. John Quinlan. C4.5: programs for machine learning. Morgan Kaufmann, San Mateo, California, 1993.
31. Daniel M. Reeves, Michael P. Wellman, Benjamin N. Grosof, and Hoi Y. Chan. Automated negotiation from declarative contract descriptions. In Seventeenth National Conference on Artificial Intelligence, Workshop on Knowledge-Based Electronic Markets (KBEM), Austin, Texas, July 30-31 2000. AAAI, AAAI Press.
32. Gurmak Singh, John O'Donoghue, and Karen Broome. An empirical study in the use of it by small and large legal firms in the uk. The Journal of Information, Law and Technology, t:http://e1j.warwick.ac.uk/jilt/02-1/singh. html, 22 March 2002. accessed 9/05/2003.
33. Sebastian Thrun et al. The MONK's problems: A performance comparison of different learning algorithms. Technical Report CMU-CS-91-197, Carnegie Mellon University, 1991.
34. David S. Wall. Information technology and the shaping of legal practice in the uk. In 13th BILETA Conference: 'The Changing Jurisdiction', page http://www.bileta.ac.uk/98papers/wall.html, 1998. accessed 9/5/2003.
35. John Zeleznikow and Dan Hunter. Building Intelligent Legal Information Systems. Computer/Law Series. Kluwer Law and Taxation Publishers, 1994.
36. John Zeleznikow and Andrew Stranieri. Knowledge discovery in the split up project. In The Sixth International Conference on Artificial Intelligence and Law, 1997.