A Temporal Argumentation Approach to Cooperative Planning Using Dialogues

  • Pere Pardo
  • Lluís Godo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8143)


In this paper, we study a dialogue-based approach to multi-agent collaborative plan search in the framework of t-DeLP, an extension of DeLP for defeasible temporal reasoning. In t-DeLP programs, temporal facts and defeasible temporal rules combine into arguments, which compare against each other to decide which of their conclusions are to prevail. A backward centralized planning system built on this logical argumentative framework has been already studied in a previous work. In this paper, we consider a distributed collaborative scenario where agents exchange information using suitable dialogues. Agents cooperate to generate arguments and actions (plan steps), and to detect argument threats to plans. We show that the soundness and completeness properties of centralized t-DeLP plan search are preserved.


Planning Domain Plan Step Plan Search Defeasible Reasoning Defeasible Logic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Amgoud, L.: A formal framework for handling conflicting desires. In: Nielsen, T.D., Zhang, N.L. (eds.) ECSQARU 2003. LNCS (LNAI), vol. 2711, pp. 552–563. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  2. 2.
    Augusto, J., Simari, G.R.: Temporal Defeasible Reasoning. Knowledge and Information Systems 3, 287–318 (2001)CrossRefzbMATHGoogle Scholar
  3. 3.
    Belesiotis, A., Rovatsos, M., Rahwan, I.: Agreeing on plans through iterated disputes. In: Proc. of AAMAS 2010, pp. 765–772 (2010)Google Scholar
  4. 4.
    Caminada, M., Amgoud, L.: On the evaluation of argumentation formalisms. Artificial Intelligence 171, 286–310 (2007)MathSciNetCrossRefzbMATHGoogle Scholar
  5. 5.
    Cobo, M.L., Martinez, D.C., Simari, G.R.: Stable Extensions in Timed Argumentation Frameworks. In: Modgil, S., Oren, N., Toni, F. (eds.) TAFA 2011. LNCS, vol. 7132, pp. 181–196. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  6. 6.
    Dung, P.: On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artificial Intelligence 77(2), 321–357 (1995)MathSciNetCrossRefzbMATHGoogle Scholar
  7. 7.
    García, D.R., García, A.J., Simari, G.R.: Defeasible Reasoning and Partial Order Planning. In: Hartmann, S., Kern-Isberner, G. (eds.) FoIKS 2008. LNCS, vol. 4932, pp. 311–328. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  8. 8.
    García, A.J., Simari, G.R.: Defeasible logic programming: An argumentative approach. Theory and Practice of Logic Programming 4(1-2), 95–138 (2004)MathSciNetCrossRefzbMATHGoogle Scholar
  9. 9.
    Ghallab, M., Nau, D., Traverso, P.: Automated Planning: Theory and Practice. Morgan Kaufmann, San Francisco (2004)Google Scholar
  10. 10.
    Hulstijn, J., van der Torre, L.: Combining goal generation and planning in an argumentation framework. In: Proc. Workshop on Argument, Dialogue and Decision at Non-monotonic Reasoning, NMR 2004 (2004)Google Scholar
  11. 11.
    Medellin-Gasque, R., Atkinson, K., McBurney, P., Bench-Capon, T.: Arguments over co-operative plans. In: Modgil, S., Oren, N., Toni, F. (eds.) TAFA 2011. LNCS, vol. 7132, pp. 50–66. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  12. 12.
    Pajares, S., Onaindia, E.: Defeasible argumentation for multi-agent planning in ambient intelligence applications. In: Proc. of AAMAS 2012, pp. 509–516 (2012)Google Scholar
  13. 13.
    Pajares, S., Onaindia, E.: Context-Aware Multi-Agent Planning in intelligent environments. Information Sciences 227, 22–42 (2013)CrossRefGoogle Scholar
  14. 14.
    Pardo, P., Godo, L.: t-DeLP: an argumentation-based Temporal Defeasible Logic Programming framework. Annals of Math. and Artif. Intel. Springer (in press)Google Scholar
  15. 15.
    Pardo, P., Godo, L.: An argumentation-based multi-agent temporal planning system built on t-DeLP. In: Proc. of CAEPIA (in Press, 2013)Google Scholar
  16. 16.
    Pardo, P., Pajares, S., Onaindia, E., Godo, L., Dellunde, P.: Multiagent argumentation for cooperative planning in DeLP-POP. In: Proc. AAMAS 2011, pp. 971–978 (2012)Google Scholar
  17. 17.
    Prakken, H.: An abstract framework for argumentation with structured arguments. Argument & Computation 1(2), 93–124 (2010)CrossRefGoogle Scholar
  18. 18.
    Rahwan, I., Pasquier, P., Sonenberg, L., Dignum, F.P.M.: On the Benefits of Exploiting Hierarchical Goals in Bilateral Automated Negotiation. In: Rahwan, I., Parsons, S., Reed, C. (eds.) ArgMAS 2007. LNCS (LNAI), vol. 4946, pp. 18–30. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  19. 19.
    Simari, G.R., Loui, R.: A mathematical treatment of defeasible reasoning and its implementation. Artificial Intelligence 53, 125–157 (1992)MathSciNetCrossRefzbMATHGoogle Scholar
  20. 20.
    Stolzenburg, F., García, A.J., Chesñevar, C., Simari, G.R.: Computing Generalized Specificity. Journal of Applied Non-Classical Logics 12(1), 1–27 (2002)Google Scholar
  21. 21.
    Tang, Y., Norman, T.J., Parsons, S.: A model for integrating dialogue and the execution of joint plans. In: McBurney, P., Rahwan, I., Parsons, S., Maudet, N. (eds.) ArgMAS 2009. LNCS, vol. 6057, pp. 60–78. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  22. 22.
    Torreño, A., Onaindia, E., Sapena, O.: An approach to multi-agent planning with incomplete information. In: Proc. of ECAI 2012, pp. 762–767. IOS Press (2012)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Pere Pardo
    • 1
    • 2
  • Lluís Godo
    • 1
  1. 1.Institut d’Investigació en Intel.ligència Artificial (IIIA - CSIC)BellaterraSpain
  2. 2.Dept. de Lògica, Hist. i Filo. CiènciaUniversitat de BarcelonaBarcelonaSpain

Personalised recommendations