A framework for multi-criteria argumentation-based decision making within a BDI agent

Authors

  • Marcelo Luis Errecalde Laboratorio de Investigación y Desarrollo en Inteligencia Computacional (LIDIC), Universidad Nacional de San Luis, San Luis, Argentina
  • Cecilia Sosa Toranzo Laboratorio de Investigación y Desarrollo en Inteligencia Computacional (LIDIC), Universidad Nacional de San Luis, San Luis, Argentina
  • Edgardo Ferretti Laboratorio de Investigación y Desarrollo en Inteligencia Computacional (LIDIC), Universidad Nacional de San Luis, San Luis, Argentina

Keywords:

Agreement Technologies, Multi-criteria Decision Making, BDI, Argumentation, Possibilistic Defeasible Logic Programming

Abstract

The BDI model, as a practical reasoning architecture aims at making decisions about what to do based on cognitives notions as beliefs, desires and intentions. However, during the decision making process, BDI agents also have to make background decisions like choosing what intention to achieve next from a set of possibly conflicting desires; which plan to execute from among the plans that satisfy a given intention; and whether is necessary or not to reconsider current intentions. With this aim, in this work, we present an abstract framework which integrates a Possibilistic Defeasible Logic Programming approach to decision making in the inner decision processes within BDI agents.

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References

[1] M. Bratman, Intentions, Plans and Practical Reason. Cambridge, MA: Harvard University Press, 1987.
[2] M. Bratman, D. Israel, and M. Pollack, “Plans and resource bounded reasoning,” Computational Intelligence, vol. 4, no. 4, pp. 349–355, 1988.
[3] D. C. Dennett, “Intentional systems,” Journal of Philosophy, vol. 68, pp. 87–106, 1971.
[4] M. Ljungberg and A. Lucas, “The oasis air traffic management system,” Tech. Rep. 28, Civil Aviation of Australia, August 1992.
[5] A. S. Rao, A. Lucas, D. Morley, M. Selvestrel, and G. Murray, “Agent-oriented architecture for air-combat simulation,” Tech. Rep. 43, Australian Artificial Intelligence Institute, 1993.
[6] R. Evertsz, M. Fletcher, R. Jones, J. Jarvis, J. Brusey, and S. Dance, Programming Multi-Agent Systems, ch. Implementing Industrial Multi-agent Systems Using JACK. Springer, 2004.
[7] S. S. Benfield, J. Hendrickson, and D. Galanti, “Making a strong business case for multiagent technology,” in 5th AAMAS, 2006.
[8] A. Casali, L. Godo, and C. Sierra, “A graded BDI agent model to represent and reason about preferences,” Artifical Intelligence, vol. 175, no. 7-8, pp. 1468–1478, 2011.
[9] L. Amgoud, “A formal framework for handling conflicting desires,” in ECSQARU (T. D. Nielsen and N. L. Zhang, eds.), vol. 2711 of Lecture Notes in Computer Science, pp. 552–563, Springer, 2003.
[10] L. Amgoud and H. Prade, “Formalizing practical reasoning under uncertainty: An argumentation-based approach,” in IAT, pp. 189–195, IEEE Computer Society, 2007.
[11] E. Ferretti, M. Errecalde, A. García, and G. Simari, “A possibilistic defeasible logic programming approach to argumentationbased decision making,” Journal of Experimental & Theoretical Artificial Intelligence, 2014. In press. Draft version at https://sites.google.com/site/edgardoferretti/TETA-2012-0093.R1.pdf?attredirects=0&d=1.
[12] N. D. Rotstein, A. J. Garc´ıa, and G. R. Simari, “Reasoning from desires to intentions: A dialectical framework,” in AAAI, pp. 136–141, AAAI Press, 2007.
[13] F. Schlesinger, E. Ferretti, M. Errecalde, and G. Aguirre, “An argumentation-based BDI personal assistant,” in IEA/AIE, vol. 6069 of LNAI, Springer, 2010.
[14] A. Garc´ıa and G. Simari, “Defeasible logic programming: an argumentative approach,” Theory and Practice of Logic Programming, vol. 4, no. 2, pp. 95–138, 2004.
[15] M. Wooldridge, Reasoning about Rational Agents. The MIT Press, 2000.
[16] D. N. Kinny, “Commitment and effectiveness of situated agents,” in In Proceedings of the Twelfth International Joint Conference on Artificial Intelligence (IJCAI-91, pp. 82–88, 1991.
[17] M. Schut and M. Wooldridge, “Intention reconsideration in complex environments,” in 4th International Conference on Autonomous Agents, 2000.
[18] S. Russell, E. Wefald, M. Karnaugh, R. Karp, D. Mcallester, D. Subramanian, and M. Wellman, “Principles of metareasoning,” Artificial Intelligence, 1991.
[19] M. E. Pollack and M. Ringuette, “Introducing the tileworld: Experimentally evaluating agent architectures,” in 8th AAAI, pp. 183–189, 1990.
[20] M. G´omez, C. Ches˜nevar, and G. Simari, “Modelling argument accrual in possibilistic defeasible logic programming,” in ECSQARU, LNCS, pp. 131–143, Springer, 2009.
[21] C. Sosa-Toranzo, F. Schlesinger, E. Ferretti, and M. Errecalde, “Integrating a voting protocol within an argumentation-based BDI system,” in XVI CACIC, 2010.

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Published

2014-04-01

How to Cite

Errecalde, M. L., Sosa Toranzo, C., & Ferretti, E. (2014). A framework for multi-criteria argumentation-based decision making within a BDI agent. Journal of Computer Science and Technology, 14(01), p. 46–54. Retrieved from https://journal.info.unlp.edu.ar/JCST/article/view/585

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Original Articles