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A Proposal for Making Argumentation Computationally Capable of Handling Large Repositories of Uncertain Data

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Scalable Uncertainty Management (SUM 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5785))

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Abstract

Data intensive applications with the capability of handling uncertain, imprecise, and inconsistent information are in constant demand. Efficient computational systems that can perform complicated inferences, obtain the appropriate conclusions, and explain the results are increasingly being required to act upon large databases. Argumentation systems could be used in the construction of interactive systems that are able to reason with large databases and/or different data sources. Notwithstanding, there are two important issues that need to be resolved in order to use argumentation in this kind of practical applications: adding the ability to deal with explicit uncertainty, and improving the computational complexity of argumentation, which so far has been an obstacle for its integration into interactive systems acting on large databases. In this paper we propose an argumentation-based system that has been engineered to address these issues.

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References

  1. Alsinet, T., Chesñevar, C.I., Godo, L., Sandri, S., Simari, G.R.: Formalizing argumentative reasoning in a possibilistic logic programming setting with fuzzy unification. International Journal of Approximate Reasoning 48(3), 711–729 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  2. Alsinet, T., Chesñevar, C.I., Godo, L., Simari, G.R.: R Simari. A logic programming framework for possibilistic argumentation: Formalization and logical properties. Fuzzy Sets and Systems 159(10), 208–228 (2008)

    Article  MATH  Google Scholar 

  3. Alsinet, T., Godo, L.: A complete calculus for possibilistic logic programming with fuzzy propositional variables. In: Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence (UAI-2000), pp. 1–10. ACM Press, New York (2000)

    Google Scholar 

  4. Berti, L.: Quality and recommendation of multi-source data for assisting technological intelligence applications. In: Proc. of 10th International Conference on Database and Expert Systems Applications, Italy, pp. 282–291. AAAI, Menlo Park (1999)

    Chapter  Google Scholar 

  5. Bryant, D., Krause, P.: An implementation of a lightweight argumentation engine for agent applications. In: Fisher, M., van der Hoek, W., Konev, B., Lisitsa, A. (eds.) JELIA 2006. LNCS (LNAI), vol. 4160, pp. 469–472. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  6. Capobianco, M., Chesñevar, C.I., Simari, G.R.: Argumentation and the dynamics of warranted beliefs in changing environments. Journal of Autonomous Agents and Multiagent Systems 11, 127–151 (2005)

    Article  Google Scholar 

  7. Carbogim, D., Robertson, D., Lee, J.: Argument-based applications to knowledge engineering. The Knowledge Engineering Review 15(2), 119–149 (2000)

    Article  MATH  Google Scholar 

  8. Chesñevar, C.I., Maguitman, A.G., Loui, R.P.: Logical Models of Argument. ACM Computing Surveys 32(4), 337–383 (2000)

    Article  Google Scholar 

  9. Chesñevar, C.I., Maguitman, A.G., Simari, G.R.: Argument-based critics and recommenders: A qualitative perspective on user support systems. Data & Knowledge Engineering 59(2), 293–319 (2006)

    Article  Google Scholar 

  10. Chesñevar, C.I., Maguitman, A.G.: ArgueNet: An Argument-Based Recommender System for Solving Web Search Queries. In: Proc. of Intl. IEEE Conference on Intelligent Systems IS-2004, Varna, Bulgaria (June 2004)

    Google Scholar 

  11. Chesñevar, C.I., Simari, G.R., Alsinet, T., Godo, L.: A logic programming framework for possibilistic argumentation with vague knowledge. In: Proc. of Uncertainty in Artificial Intelligence Conference (UAI 2004), Banff, Canada (2004) (to appear)

    Google Scholar 

  12. Doyle, J.: A Truth Maintenance System. Artificial Intelligence 12(3), 231–272 (1979)

    Article  MathSciNet  Google Scholar 

  13. Dubois, D., Lang, J., Prade, H.: Possibilistic logic. In: Gabbay, D., Hogger, C., Robinson, J. (eds.) Handbook of Logic in Art. Int. and Logic Prog. (Nonmonotonic Reasoning and Uncertain Reasoning), pp. 439–513. Oxford Univ. Press, Oxford (1994)

    Google Scholar 

  14. García, A., Simari, G.: Defeasible Logic Programming: An Argumentative Approach. Theory and Practice of Logic Programming 4(1), 95–138 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  15. Gelfond, M., Lifschitz, V.: Classical negation in logic programs and disjunctive databases. New Generation Computing, 365–385 (1991)

    Google Scholar 

  16. Gomez, S.A., Chesñevar, C.I.: A Hybrid Approach to Pattern Classification Using Neural Networks and Defeasible Argumentation. In: Proc. of Intl. 17th FLAIRS Conference, Palm Beach, FL, USA, May 2004, pp. 393–398. AAAI, Menlo Park (2004)

    Google Scholar 

  17. Katsuno, H., Mendelzon, A.: On the difference between updating a knowledge base and revising it. In: Gardenfors, P. (ed.) Belief Revision, pp. 183–203. Cambridge University Press, Cambridge (1992)

    Chapter  Google Scholar 

  18. Prakken, H., Vreeswijk, G.: Logical systems for defeasible argumentation. In: Handbook of Philosophical Logic, vol. 4, pp. 219–318 (2002)

    Google Scholar 

  19. Rahwan, I., Ramchurn, S.D., Jennings, N.R., McBurney, P., Parsons, S., Sonenberg, L.: Argumentation-based negotiation. The Knowledge Engineering Review 18(4), 343–375 (2003)

    Article  Google Scholar 

  20. Simari, G.R., Loui, R.P.: A Mathematical Treatment of Defeasible Reasoning and its Implementation. Artificial Intelligence 53(1–2), 125–157 (1992)

    Article  MathSciNet  MATH  Google Scholar 

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Capobianco, M., Simari, G.R. (2009). A Proposal for Making Argumentation Computationally Capable of Handling Large Repositories of Uncertain Data. In: Godo, L., Pugliese, A. (eds) Scalable Uncertainty Management. SUM 2009. Lecture Notes in Computer Science(), vol 5785. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04388-8_9

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  • DOI: https://doi.org/10.1007/978-3-642-04388-8_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04387-1

  • Online ISBN: 978-3-642-04388-8

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