Introduction to inconsistency tolerance

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3300 LNCS, Issue , 2004, Pages 1-14

  Bertossi, Leopoldo ^a   Hunter, Anthony ^b   Schaub, Torsten ^c,d  

^a CARLETON UNIVERSITY   (Canada)

^b UNIVERSITY COLLEGE LONDON   (United Kingdom)

^c Institut fur Informatik   (Germany)

^d SIMON FRASER UNIVERSITY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SUPPORTED COOPERATIVE WORK; INFORMATION ANALYSIS; NATURAL LANGUAGE PROCESSING SYSTEMS; ROBOTICS; SENSOR DATA FUSION; APPLICATION PROGRAMS; MERGING;

COMMONSENSE REASONING; INCONSISTENCY TOLERANCE; NATURAL LANGUAGE DIALOGUES;

MULTI AGENT SYSTEMS;

ANALYSING INCONSISTENCY; APPLICATION TECHNOLOGIES; BRAINSTORMING SESSIONS; HETEROGENEOUS SOURCES; INCONSISTENCY TOLERANCES; INCONSISTENT INFORMATION; NATURAL LANGUAGE DIALOGUE; RESEARCH COLLABORATIONS;

EID: 36849012533     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: None     Document Type: Conference Paper

References (72)

1. C Alchourron, P Gardenfors, and D Makinson. On the logic of theory change: partial meet contraction and revision functions. Journal of Symbolic Logic, 50:510-530, 1985.
2. L Amgoud and C Cayrol. On the acceptability of arguments in preference-based argumentation. In G Cooper and S Moral, editors, Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence. Morgan Kaufmann, 1998.
3. M Arenas, L Bertossi, and J Chomicki. Consistent query answers in inconsistent databases. In Proc. ACM Symposium on Principles of Database Systems (PODS 99), pages 68-79, 1999.
4. O Arieli and A. Avron. The value of the four values. Artificial Intelligence, 102:97-141, 1998.
5. D Batens. Paraconsistent extensional propositional logics. Logique et Analyse, 90-91:195-234, 1980.
6. N Belnap. A useful four-valued logic. In G Epstein, editor, Modern Uses of Multiple-valued Logic, pages 8-37. Reidel, 1977.
7. S Benferhat, D Dubois, and H Prade. Argumentative inference in uncertain and inconsistent knowledge bases. In Proceedings of Uncertainty in Artificial Intelligence, pages 1449-1445. Morgan Kaufmann, 1993.
8. S Benferhat, D Dubois, and H Prade. A logical approach to reasoning under inconsistency in stratified knowledge bases. In Symbolic and Quantitative Approaches to Reasoning and Uncertainty, volume 956 of Lecture Notes in Computer Science, pages 36-43. Springer, 1995.
9. L Bertossi and J Chomicki. Query answering in inconsistent databases. In G Saake J Chomicki and R van der Meyden, editors, Logics for Emerging Applications of Databases. Springer, 2003.
10. Philippe Besnard and Torsten Schaub. Signed systems for paraconsistent reasoning. Journal of Automated Reasoning, 20:191-213, 1998.
11. Ph Besnard and A Hunter. Quasi-classical logic: Non-trivializable classical reasoning from inconsistent information. In C Proidevaux and J Kohlas, editors, Symbolic and Quantitative Approaches to Uncertainty, volume 946 of Lecture Notes in Computer Science, pages 44-51, 1995.
12. Ph Besnard and A Hunter. A logic-based theory of deductive arguments. Artificial Intelligence, 128:203-235, 2001.
13. J Blakeley, N Coburn, and P Larson. Updating derived relations: detecting irrelevant and autonomously computable updates. ACM Transactions on Database Systems, 14(3):369-400, 1989.
14. G Brewka. Preferred subtheories: An extended logical framework for default reasoning. In Proceedings of the Eleventh International Conference on Artificial Intelligence, pages 1043-1048, 1989.
15. D Carbogim, D Robertson, and J Lee. Argument-based applications to knowledge engineering. Knowledge Engineering Review, 15:119-149, 2000.
16. S Ceri, P Fraternali, S Paraboschi, and L Tanca. Automatic generation of production rules for integrity maintenance. ACM Transactions on Database Systems, 19(3):367-422, 1994.
17. C Chesnevar, A Maguitman, and R Loui. Logical models of argument. ACM Computing Surveys, 32:337-383, 2001.
18. A Darwiche and J Pearl. On the logic of iterated belief revision. Artificial Intelligence, 89:1-29, 1997.
19. A Darwiche. Compiling knowledge into decomposible negation normal form. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAP99), pages 284-289, 1999.
20. M. Davis and H. Putnam. A computing procedure for quantification theory. Journal of the ACM, 7:201-215, 1960.
21. N C da Costa. On the theory of inconsistent formal systems. Notre Dame Journal of Formal Logic, 15:497-510, 1974.
22. R Dechter and J Pearl. Network-based heuristics for constraint- satisfaction problems. Artificial Intelligence, 34:1-38, 1987.
23. D Dubois and H Prade, editors. Handbook of Defeasible Resoning and Uncertainty Management Systems, volume 3. Kluwer, 1998.
24. P. Dung. On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artificial Intelligence, 77:321-357, 1995.
25. M Elvang-Goransson and A Hunter. Argumentative logics: Reasoning from classically inconsistent information. Data and Knowledge Engineering, 16:125-145, 1995.
26. J Fox and S Das. Safe and Sound: Artificial Intelligence in Hazardous Applications. MIT Press, 2000.
27. D Gabbay and A Hunter. Making inconsistency respectable 1: A logical framework for inconsistency in reasoning. In Fundamentals of Artificial Intelligence, volume 535 of Lecture Notes in Computer Science, pages 19-32. Springer, 1991.
28. D Gabbay and O Rodrigues. A methodology for iterated theory change. In Practical Reasoning, volume 1085 of Lecture Notes in Computer Science. Springer, 1996.
29. P Gardenfors. Knowledge in Flux. MIT Press, 1988.
30. M Garey and D Johnson. Computers and Intractability: A Guide to the Theory of NP-Completeness. Freeman, 1979.
31. J Gebhardt and R Kruse. Background and perspectives of possibilistic graphical models. In A Hunter and S Parsons, editors, Applications of Uncertainty Formalisms, Lecture Notes in Computer Science. Springer, 1998.
32. M Gertz and W Lipeck. An extensible framework for repairing constraint violations. In S Jajodia et al., editor, Integrity and Internal Control in Information Systems, IFIP TC11 Working Group 11.5, First Working Conference on Integrity and Internal Control in Information Systems: Increasing the confidence in Information Systems, Zurich, Switzerland, December 4-5, 1997, pages 89-111. Chapman Hall, 1997.
33. J Grant. Classifications for inconsistent theories. Notre Dame Journal of Formal Logic, 19:435-444, 1978.
34. R Haenni, J Kohlas, and N Lehmann. Probabilistic argumentation systems. In D Gabbay and Ph Smets, editors, Handbook of Defeasible Reasoning and Uncertainty Management Systems, Volume 5, pages 221-288. Kluwer, 2000.
35. A Hunter. Reasoning with contradictory information using quasi-classical logic. Journal of Logic and Computation, 10:677-703, 2000.
36. A Hunter. A semantic tableau version of first-order quasi-classical logic. In Quantitative and Qualitative Approaches to Reasoning with Uncertainty, LNCS. Springer, 2001. 544-556.
37. A Hunter. Measuring inconsistency in knowledge via quasi-classical models. In Proceedings of the 18th National Conference on Artificial Intelligence (AAAI'2002), pages 68-73. MIT Press, 2002. ISBN 0-262-51129-0.
38. A Hunter. Evaluating the significance of inconsistency. In Proceedings of the International Joint Conference on AI (IJCAI'03), pages 468-473, 2003.
39. A Hunter. Logical comparison of inconsistent perspectives using scoring functions. Knowledge and Information Systems Journal, 2004. (in press).
40. A Hunter. Probable consistency checking for sets of propositional clauses. In Symbolic and Quantitative Approaches to Reasoning with Uncertainty, volume 2711 of Lecture Notes in Computer Science. Springer, 2003. pages 464 - 476.
41. H Katsuno and A Mendelzon. On the difference between updating a knowledgebase and revising it. Belief Revision, pages 183-203, 1992.
42. K Knight. Measuring inconsistency. Journal of Philosophical Logic, 31:77-98, 2001.
43. K Knight. Two information measures for inconsistent sets. Journal of Logic, Language and Information, 12:227-248, 2003.
44. S Konieczny, J Lang, and P Marquis. Quantifying information and contradiction in propositional logic through epistemic actions. In Proceedings of the 18th International Joint Conference on Artificial Intellignce (IJCAI'03), 2003. in press.
45. S Konieczny and R Pino Perez. On the logic of merging. In Proceedings of the Sixth International Conference on Principles of Knowledge Representation and Reasoning (KR98), pages 488-498. Morgan Kaufmann, 1998.
46. S Konieczny and R Pino Perez. Merging with integrity constraints. In Anthony Hunter and Simon Parsons, editors, Qualitative and Quantitative Approaches to Reasoning and Uncertainty (ECSQARU'99), volume 1638 of Lecture Notes in Computer Science. Springer, 1999.
47. E Laenens and D Vermeir. A fixpoint semantics for ordered logic. Journal of Logic and Computation, 1:159-185, 1990.
48. D Lehmann. Belief revision, revised. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'95), pages 1534-1540, 1995.
49. H Levesque. A logic of implicit and explicit belief. In Proceedings of the National Conference on Artificial Intelligence (AAAI'84), pages 198-202, 1984.
50. P Liberatore and M Schaerf. Arbitration (or how to merge knowledgebases). IEEE Transactions on Knowledge and Data Engineering, 10:76-90, 1998.
51. E Lozinskii. Information and evidence in logic systems. Journal of Experimental and Theoretical Artificial Intelligence, 6:163-193, 1994.
52. R Manor and N Rescher. On inferences from inconsistent information. Theory and Decision, 1:179-219, 1970.
53. P Marquis. Knowledge compilation using prime implicates. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'95), pages 837843, 1995.
54. J-M. Nicolas. Logic for improving integrity checking in relational data bases. Acta Informatica, 18:227-253, 1982.
55. D Nute. Defeasible reasoning and decision support systems. Decision Support Systems, 4:97-110, 1988.
56. F Oppacher and E Suen. HARP: A tableau-based theorem prover. Journal of Automated Reasoning, 4:69-100, 1988.
57. C Papadimitriou. Computational Complexity. Addison-Wesley, 1994.
58. S Parsons, C Sierra, and N Jennings. Agents that reason and negotiate by arguing. Journal of Logic and Computation, 8:261-292, 1998.
59. J Pollock. Defeasible reasoning. Cognitive Science, 11:481-518, 1987.
60. J Pollock. How to reason defeasibly. Artificial Intelligence, 57:1-42, 1992.
61. H Prakken and G Vreeswijk. Logical systems for defeasible argumentation. In D Gabbay, editor, Handbook of Philosophical Logic. Kluwer, 2000.
62. H Prakken. Logical Tools for Modelling Legal Argument. Kluwer, 1997.
63. G Priest. Reasoning abuot truth. Artificial Intelligence, 39:231-244, 1989.
64. R Reiter. Towards a logical reconstruction of relational database theory. In M.Brodie, J.Mylopoulos, and J. Schmidt, editors, On Conceptual Modeling, pages 191-233. Springer-Verlag, 1984.
65. M Ryan. Representing defaults as sentences with reduced priority. In Principles of Knowledge Representation and Reasoning: Proceedings of the Third International Conference. Morgan Kaufmann, 1992.
66. M Schaerf and M Cadoli. Tractable reasoning via approximation. Artificial Intelligence, 74:249-310, 1995.
67. B Selman, H Levesque, and D Mitchell. A new method for solving hard satisfiability problems. In Proceedings of the Tenth National Conference on Artificial Intelligence (AAAI'92), pages 440-446, 1992.
68. B. Selman, H. Levesque, and D. Mitchell. A new method for solving hard satisfiability problems. In P. Rosenbloom and P. Szolovits, editors, Proceedings of AAAI'92, pages 440-446. AAAI Press, 1992.
69. C Shannon. A mathematical theory of communication. Bell System Technical Journal, 27:379-423, 1948.
70. D Vermeir, E Laenens, and P Geerts. Defeasible logics. In Handbook of Defeasible Reasoning and Uncertainty Management, volume 2. Kluwer, 1998.
71. G Vreeswijk. Abstract argumentation systems. Artificial Intelligence, 90:225-279, 1997.
72. P Wong and Ph Besnard. Paraconsistent reasoning as an analytic tool. Journal of the Interest Group in Propositional Logic, 9:233-246, 2001.