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Semantics for a theory of defeasible reasoning

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Abstract

In this paper, we establish a formal semantics for Pollock’s [23] theory of defeasible reasoning. As a notion of argument or argumentation has never been formalised in this theory, it is important that such a formal account be introduced to couple with the algorithmic description of the theory. In particular, it makes Pollock’s theory become more comparable to other related frameworks as shown in the paper. In also enforces a well-defined semantical account for Pollock’s theory of defeasible reasoning based on the argumentation-theoretic approach proposed by Dung and Bondarenko et al. [1,5]. Our formalisation thus enables further studies to the meta-theoretic properties of Pollock’s defeasible reasoning system.

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References

  1. A. Bondarenko, P.M. Dung, R.A. Kowalski and F. Toni, An abstract, argumentation-theoretic approach to default reasoning, Artificial Intelligence Journal 93 (1997) 63–101.

    Google Scholar 

  2. C.I. Chesñevar, A.G. Maguitman and R.P. Loui, Logical models of argument, ACM Computing Surveys (CSUR) 32(4) (2000) 337–383.

    Google Scholar 

  3. Y. Dimopoulos, B. Nebel and F. Toni, Preferred arguments are harder to compute than stable extensions, in: International Joint Conference on Artificial Intelligence, Stockholm, Sweden (1999) pp. 36–43.

  4. J. Doyle, A truth maintenance system, Artificial Intelligence Journal 12(3) (1979) 231–272.

    Google Scholar 

  5. P.M. Dung, The acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games, Artificial Intelligence Journal 77 (1995) 321–357.

    Google Scholar 

  6. P.M. Dung, An argumentation-theoretic foundations for logic programming, Journal of Logic Programming 22(2) (1995) 151–171.

    Google Scholar 

  7. P.M. Dung and T.C. Son, An argument-based approach to reasoning with specificity, Artificial Intelligence Journal 133(1–2) (2001) 35–85.

    Google Scholar 

  8. D. Gabbay, C. Hogger and J. Robinson (eds.), Nonmonotonic Reasoning and Uncertain Reasoning, Handbook of Logic in Artificial Intelligence and Logic Programming, Vol. 3 (Oxford University Press, Oxford, 1994).

    Google Scholar 

  9. M. Gelfond and V. Lifschitz, The stable model semantics for logic programming, in: Proceedings of the Fifth International Conference and Symposium on Logic Programming (1988) pp. 1070–1080.

  10. M. Ginsberg (ed.), Readings in Nonmonotonic Reasoning (Morgan Kauffman, Los Altos, CA, 1987).

    Google Scholar 

  11. J.F. Horty, Some direct theories of nonmonotonic inheritance, in: Nonmonotonic Reasoning and Uncertain Reasoning, eds. D. Gabbay, C. Hogger and J. Robinson, Handbook of Logic in Artificial Intelligence and Logic Programming, Vol. 3 (Oxford University Press, Oxford, 1994) pp. 111–187.

    Google Scholar 

  12. K. Konolige, On the relation between default theories and autoepistemic logic, in: International Joint Conference on Artificial Intelligence (1987) pp. 394–400.

  13. F. Lin and Y. Shoham, Argument systems: A uniform basis for nonmonotonic reasoning, in: Principles of Knowledge Representation and Reasoning, Toronto, Canada (1989) pp. 245–255.

  14. R. Loui, Defeat among arguments: a system of defeasible inference, Journal of Computational Intelligence 2 (1987) 100–106.

    Google Scholar 

  15. J. McCarthy, Circumscription – a form of nonmonotonic reasoning, Artificial Intelligence Journal 13(1–2) (1980) 27–39.

    Google Scholar 

  16. J. McCarthy, Applications of circumscription to formalizing common sense knowledge, Artificial Intelligence Journal 26(3) (1986) 89–116.

    Google Scholar 

  17. D.V. McDermott and J. Doyle, Non-monotonic logic I, Artificial Intelligence Journal 13(12) (1980) 41–72.

    Google Scholar 

  18. R.C. Moore, Semantical considerations on nonmonotonic logic, Artificial Intelligence Journal 25(1) (1985) 75–94.

    Google Scholar 

  19. D.N. Nute, Defeasible logic, in: Nonmonotonic Reasoning and Uncertain Reasoning, eds. D.M. Gabbay, C.G. Hogger and J.A. Robinson, Handbook of Logic in Artificial Intelligence and Logic Programming, Vol. 3 (Oxford University Press, Oxford, 1994).

    Google Scholar 

  20. J. Pollock, Knowledge and Justification (Princeton University Press, Princeton, 1974).

    Google Scholar 

  21. J. Pollock, Defeasible reasoning, Cognitive Science 11 (1987) 481–518.

    Google Scholar 

  22. J. Pollock, Justification and defeat, Artificial Intelligence Journal 67 (1994) 377–408.

    Google Scholar 

  23. J. Pollock, Cognitive Carpentry: A Blueprint for How to Build a Person (MIT Press, London, 1995).

    Google Scholar 

  24. J. Pollock, Defeasible reasoning with variable degrees of justification, Artificial Intelligence Journal 133(1–2) (2001) 233–282.

    Google Scholar 

  25. D. Poole, A logical framework for default reasoning, Artificial Intelligence Journal 36(1) (1988) 27–47.

    Google Scholar 

  26. H. Prakken and G. Sartor, A dialectical model of assessing conflicting arguments in legal reasoning, Artificial Intelligence and Law 4(3–4) (1996) 331–368.

    Google Scholar 

  27. H. Prakken and G. Sartor, Argument-based extended logic programming with defeasible priorities, Journal of Applied Non-Classical Logics 7 (1997) 25–75.

    Google Scholar 

  28. H. Prakken and G. Vreeswijk, Logics for defeasible argumentation, in: Handbook of Philosophical Logic, 2nd edition, Vol. 5, eds. D. Gabbay and F. Guenther (Kluwer Academic Publishers, Dordrecht, 2001).

    Google Scholar 

  29. R. Reiter, A logic for default reasoning, Artificial Intelligence Journal 13 (1980) 81–132.

    Google Scholar 

  30. G.R. Simari and R.P. Loui, A mathematical treatment of defeasible reasoning and its implementation, Artificial Intelligence Journal 53(2–3) (1992) 125–157.

    Google Scholar 

  31. Q.B. Vo, Meta-constructs and their roles in common sense reasoning, PhD thesis, School of Computer Science and Engineering, University of New South Wales (2002).

  32. Q.B. Vo and N.Y. Foo, Solving the qualification problem, in: Australian Joint Conference on Artificial Intelligence (2001) pp. 519–531.

  33. Q.B. Vo and N.Y. Foo, Solving the ramification problem: Causal propagation in an argumentation-theoretic approach, in: 7th Pacific Rim International Conference on Artificial Intelligence – PRICAI2002 (2002) pp. 49–59.

  34. Q.B. Vo and J. Thurbon, Semantics for Pollock’s defeasible reasoning, in: Australian Joint Conference on Artificial Intelligence (1999) pp. 316–327.

  35. G.A.W. Vreeswijk, Studies in deafeasible argumentation, PhD thesis, Department of Computer Science, Free University of Amsterdam (1993).

  36. G.A.W. Vreeswijk, Abstract argumentation systems, Artificial Intelligence Journal 90 (1997) 225–279.

    Google Scholar 

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Correspondence to Quoc Bao Vo.

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AMS (MOS) classification

68T30, 68T27

Part of the work presented in this paper has appeared in [34].

This work was performed while the first and the third authors were at the School of Computer Science and Engineering, University of New South Wales.

Quoc Bao Vo: Supported by the Dialog project, Collaborative Research Centre on Resource-adaptive cognitive processes (DFG-SFB378).

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Vo, Q.B., Foo, N.Y. & Thurbon, J. Semantics for a theory of defeasible reasoning. Ann Math Artif Intell 44, 87–119 (2005). https://doi.org/10.1007/s10472-005-1807-4

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