Article

Article title ARGUMENTATION WITH DEGREES OF JUSTIFICATION IN INTELLIGENT SYSTEMS
Authors O.L. Morosin
Section SECTION III. ARTIFICIAL INTELLECT AND INDISTINCT SYSTEMS
Month, Year 07, 2014 @en
Index UDC 004.832.3
DOI
Abstract This paper provides a brief overview of approaches to the formalization of argumentation systems. Opportunities of application of justification degrees are also observed. Justification degrees allow us to solve various argumentation problems that need numerical estimation of an answer. In contrast to classical logic, defeasible reasoning allows us to draw conclusions on the contradictory and incomplete sets of propositions. All conclusions are not considered as reliable and may be revised at a later stage of reasoning when new knowledge (or even new conclusions from existing knowledge) appears. In addition, it is given an example of a task, which is not solvable in classical logics terms.

Download PDF

Keywords Defeasible reasoning; argumentation; natural deduction; non-monotonic reasoning; degrees of justification.
References 1. Philippe Besnard and Anthony Hunter. Elements of argumentation. Cambridge: MIT press, 2008, 298 p.
2. Bondarenko A., Dung P.M., Kowalski R.A., Toni F. An abstract argumentation-theoretic framework for defeasible reasoning, Ibid, 1997, Vol. 93(1-2), pp. 63-101.
3. Lin F., Shoham Y. Argument systems. A uniform basis for nonmonotonic reasoning, Proc. Of the First Int. Conf. on Principles of Knoledge Representation and Reasoning. San Mateo, CA: Morgan Kaufmann Publishers Inc, 1989, pp. 245-355.
4. Vreeswijk G.A.W. Abstract argumentation systems, Artificial Intelligence, 1997, Vol. 90, pp. 225-279.
5. John L. Pollock. How to Reason Defeasibly, Artificial Intelligence, 1992, No. 57, pp. 1-42.
6. Vagin V.N., Golovina E.Yu., Zagoryanskaya A.A., Fomina M.V. Dostovernyy i pravdopodobnyy vyvod v intellektualnykh sistemakh [Reliable and plausible conclusion in intelligent systems]. 2-e izdanie dopolnennoe i ispravlennoe. Moscow: Fizmatlit, 2008, 712 p.
7. John L. Pollock. Defeasible Reasoning. Reasoning: Studies of Human Inference and its Foundations, ed. Jonathan Adler and Lance Rips, Cambridge University Press, 2006, pp. 31.
8. John L. Pollock. Natural Deduction. Technical Report, Department of Philosophy, University of Arizona, Tucson, 1996, 35 p.
9. John L. Pollock. Defeasible reasoning with variable degrees of justification, Artificial Intelligence, 2001, Vol. 133, pp. 233-282.
10. Haenni R., Kohlas J., Lehmann N. Probabilistic Argumentation Systems, Handbook of Defeasible Reasoning and Uncertainty Management Systems, Dordrecht: Vol. 5: Algorithms for Uncertainty and Defeasible Reasoning, Kluwer. 1999, pp. 221-287.
11. Gerard A.W. Vreeswijk. Interpolation of Benchmark Problems in Defeasible Reasoning, Wocfai, 1995, pp. 453-468.

Comments are closed.