Value-based argumentation frameworks as neural-symbolic learning systems

Journal of Logic and Computation

Volumn 15, Issue 6, 2005, Pages 1041-1058

  Garcez, Artur S D'Avila ^a   Gabbay, Dov M ^b   Lamb, Luis C ^c  

^a CITY UNIVERSITY   (United Kingdom)

^b KING'S COLLEGE LONDON   (United Kingdom)

^c FEDERAL UNIVERSITY OF RIO GRANDE DO SUL   (Brazil)

Author keywords

Hybrid systems; Neural symbolic systems; Value based argumentation frameworks

Indexed keywords

ALGORITHMS; COMPUTATIONAL METHODS; FORMAL LOGIC; NEURAL NETWORKS; STANDARDS;

ARGUMENTATION ALGORITHMS; HYBRID SYSTEMS; NEURAL-SYMBOLIC SYSTEMS; VALUE-BASED ARGUMENTATION FRAMEWORKS;

LEARNING SYSTEMS;

EID: 29144436730     PISSN: 0955792X     EISSN: 1465363X     Source Type: Journal    
DOI: 10.1093/logcom/exi057     Document Type: Article

References (35)

1. G. Antoniou. Nonmonotonic Reasoning. MIT Press, Cambridge, MA, 1997.
2. K. R. Apt and D. Pedreschi. Reasoning about termination of pure prolog programs. Information and Computation, 106, 109-157, 1993.
3. H. Barringer, D. M. Gabbay and J. Woods. Temporal dynamics of support and attack networks: From argumentation to zoology. In Mechanizing Mathematical Reasoning: Essays in Honor of Joerg H. Siekmann, D. Hutter and W. Stephan, eds, pp. 59-98. Springer-Verlag, 2005.
4. T. J. M. Bench-Capon. Persuasion in practical argument using value-based argumentation frameworks. Journal of Logic and Computation, 13, 429-448, 2003.
5. P. Besnard and A. Hunter. Towards a logic-based theory of argumentation. In Proceedintgs of 17th National Conference on Artificial Intelligence AAAI'00, pp. 411-416. AAAI Press, 2000.
6. A. Bondarenko, P. Dung, R. Kowalski, and F. Toni. An abstract, argumentation theoretic approach to default reasoning. Artificial Intelligence, 93, 63-101, 1997.
7. N. K. Bose and P. Liang. Neural Networks Fundamentals with Graphs, Algorithms, and Applications. McGraw-Hill, 1996.
8. G. Brewka. Dynamic argument systems: A formal model of argumentation processes based on situation calculus. Journal of Logic and Computation, 11, 257-282, 2001.
9. C. I. Chesñevar, A. G. Maguitman, and R. P. Loui. Logical Models of Argument. ACM Computing Surveys, 32, 337-383, 2000.
10. A. S. d' Avila Garcez, K. Broda, and D. M. Gabbay. Symbolic knowledge extraction from trained neural networks: A sound approach. Artificial Intelligence, 125, 155-207, 2001.
11. A. S. d'Avila Garcez, K. Broda, and D. M. Gabbay. Neural-Symbolic Learning Systems: Foundations and Applications. Springer-Verlag, 2002.
12. A. S. d'Avila Garcez and D. M. Gabbay. Fibring neural networks. In Proceedings of 19th National Conference on Artificial Intelligence AAAI'04, pp. 342-347, San Jose, California, USA, July 2004. AAAI Press.
13. A. S. d'Avila Garcez and L. C. Lamb. Reasoning about time and knowledge in neural-symbolic learning systems. In Advances in Neural Information Processing Systems 16, Proceedings of the NIPS 2003 Conference, S. Thrun, L. Saul, and B. Schoelkopf, eds, pp. 921-928. MIT Press, Cambridge, MA, 2004.
14. A. S. d'Avila Garcez, L. C. Lamb, K. Broda, and D. M. Gabbay. Applying connectionist modal logics to distributed knowledge representation problems. International Journal on Artificial Intelligence Tools, 13(1):115-139, 2004.
15. P. M. 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.
16. D. M. Gabbay and J. Woods. The law of evidence and labelled deduction: A position paper. Phi News, 4, 5-46, 2003.
17. A. J. García and G. R. Simari. Defeasible logic programming: An argumentative approach. Theory and Practice of Logic Programming, 4, 95-138, 2004.
18. M. Gelfond and V. Lifschitz. The stable model semantics for logic programming. In Proceedings of the 5th Logic Programming Symposium, pp. 1070-1080, 1988.
19. R. Haenni, J. Kohlas, and N. Lehmann. Probabilistic argumentation systems. In Handbook of Defeasible Reasoning and Uncertainty Management Systems, volume 5, J. Kohlas and S. Moral, eds. Kluwer, 2000.
20. S. Haykin. Neural Networks: A Comprehensive Foundation. Prentice Hall, 1999.
21. S. Holldobler and Y. Kalinke. Toward a new massively parallel computational model for logic programming. In Proceedings of the Workshop on Combining Symbolic and Connectionist Processing, ECAI 94, pp. 68-77, 1994.
22. R. Kowalski and F. Toni. Abstract argumentation. Artificial Intelligence and Law, 4, 275-296, 1996.
23. J. W. Lloyd. Foundations of Logic Programming. Springer-Verlag, 1987.
24. T. M. Mitchell. Machine Learning. McGraw-Hill, 1997.
25. D.Nute. Defeasible logic. In. Handbook of Logic in Artificial Intelligence and Logic Programming, Vol 3, D.M. Gabbay, C.J. Hogger, and J.A.Robinson, eds, pp. 355-395. Oxford University Press, 1994.
26. J. Pollock. Defeasible Reasoning. Cognitive Science, 11, 481-518, 1987.
27. J. Pollock. Self-defeating arguments. Minds and Machines, 1, 367-392, 1991.
28. H. Prakken and G. A. W. Vreeswijk. Logical systems for defeasible argumentation. In Handbook of Philosophical Logic, D. Gabbay and F. Guenthner, eds. Kluwer, 2nd edition, 2000.
29. D. E. Rumelhart, G. E. Hinton and R. J. Williams. Learning internal representations by error propagation. In Parallel Distributed Processing, volume 1, pp. 318-362. MIT Press, 1986.
30. G. G. Towell and J. W. Shavlik. Knowledge-based artificial neural networks. Artificial Intelligence, 70, 119-165, 1994.
31. L.G. Valiant. Three problems in computer science. Journal of the ACM, 50, 96-99, 2003.
32. B. Verheij. Accrual of arguments in defeasible argumentation. In Proceedings of 2nd Dutch/German Workshop on Nonmonotonic Reasoning, pp. 217-224. Utrecht, 1995.
33. B. Verheij. Rules, Reasons, Arguments; Formal Studies of Argumentation and Defeat. PhD thesis, Maastricht University, Holland, 1996.
34. G. A. W. Vreeswijk. Abstract argumentation systems. Artificial Intelligence, 90, 225-279, 1997.
35. J. Williamson and D. Gabbay. Recursive causality in bayesian networks and self-fibring networks. In Laws and Models in Science, D. Gillies, ed. King's College Publications, London, 2004.