Learning of Defaults by Agents in a Distributed Multi-Agent System Environment

  • Henryk Rybinski
  • Dominik Ryżko
  • Przemysław Więch
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 13)


The paper introduces a novel approach to machine learning in a multi-agents system. A distributed version of Inductive Logic Programming is used, which allows agents to construct new rules based on knowledge and examples, which are available to different memebrs of the system. The learning process is performed in two phases – first locally by each agent and then on the global level while reasoning.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Alonso, E., D’Inverno, M., Kudenko, D., Luck, M., Noble, J.: Learning in multi-agent systems. Knowledge Engineering Review 16, 277–284 (2001)CrossRefGoogle Scholar
  2. 2.
    Antonelli, G.A.: A directly cautious theory of defeasible consequence for default logic via the notion of general extension. Artificial Intelligence 109, 71–109 (1999)MathSciNetMATHCrossRefGoogle Scholar
  3. 3.
    Benferhat, S., Dubois, D., Lagrue, S., Prade, H.: Towards Learning Default Rules by Identifying Big-Stepped Probabilities. In: IFSA World Congress (2002)Google Scholar
  4. 4.
    Bratko, I.: Applications of inductive logic programming. Communications of the ACM 38(11) (November 1995)Google Scholar
  5. 5.
    Dimopoulos, Y., Kakas, A.: Learning Non-Monotonic Logic Programs: Learning Exceptions. In: Lavrač, N., Wrobel, S. (eds.) ECML 1995. LNCS, vol. 912, pp. 122–137. Springer, Heidelberg (1995)CrossRefGoogle Scholar
  6. 6.
    Duval, B., Nicolas, P.: Learning Default Theories. In: Hunter, A., Parsons, S. (eds.) ECSQARU 1999. LNCS (LNAI), vol. 1638, pp. 148–159. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  7. 7.
    Fonseca, N.A., Silva, F., Camacho, R.: Strategies to Parallelize ILP Systems. In: Kramer, S., Pfahringer, B. (eds.) ILP 2005. LNCS (LNAI), vol. 3625, pp. 136–153. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  8. 8.
    Governatori, G., Stranieri, A.: Towards the application of association rules for defeasible rules discovery. In: Verheij, B., Lodder, A., Loui, R.P., Muntjerwerff, A.J. (eds.) Legal Knowledge and Information Systems, pp. 63–75. IOS Press, Amsterdam (2001)Google Scholar
  9. 9.
    Inoue, K., Kudoh, Y.: Learning Extended Logic Programs. In: Proc. of the 15th IJCAI, vol. 1, pp. 176–181. Morgan Kaufmann (1997)Google Scholar
  10. 10.
    Johnston, B., Governatori, G.: An algorithm for the induction of defeasible logic theories from databases. In: Schewe, K.-D., Zhou, X. (eds.) Conference Research and Practice of Information Technology, Database Technology 2003, Australian Computer Science Association, ACS, vol. 17, pp. 75–83 (2003)Google Scholar
  11. 11.
    Kazakov, D., Kudenko, D.: Machine Learning and Inductive Logic Programming for Multi-Agent Systems. In: Luck, M., Mařík, V., Štěpánková, O., Trappl, R. (eds.) ACAI 2001 and EASSS 2001. LNCS (LNAI), vol. 2086, pp. 246–270. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  12. 12.
    Lukaszewicz, W.: Considerations on default logic: An alternative approach. Computational Intelligence 4(1), 1–16 (1988)MathSciNetCrossRefGoogle Scholar
  13. 13.
    Muggleton, S.: Inductive Logic Programming. New Generation Computing 8(4), 295–318 (1991)MATHCrossRefGoogle Scholar
  14. 14.
    Muggleton, S., de Raedt, L.: Inductive Logic Programming: Theory and methods. The Journal of Logic Programming 19-20(suppl.1), 629–679 (1994)CrossRefGoogle Scholar
  15. 15.
    Nienhuys-Cheng, S.-H., de Wolf, R. (eds.): Foundations of Inductive Logic Programming. LNCS(LNAI), vol. 1228. Springer, Heidelberg (1997)Google Scholar
  16. 16.
    Przymusiǹska, H., Przymusiǹski, T.: Stationary Default Extensions. Fundamenta Informaticae 21, 67–87 (1994)MathSciNetGoogle Scholar
  17. 17.
    Reiter, R.: A Logic for Default Reasoning. In: Artificial Intelligence, vol. 13, pp. 81–132 (1980)Google Scholar
  18. 18.
    Ryżko, D., Rybinski, H.: Distributed Default Logic for Multi-Agent System. In: Proc. WI/IAT (2003)Google Scholar
  19. 19.
    Sakama, C., Inoue, K.: Prioritized logic programming and its application to commonsense reasoning. In: AI, vol. 123(1-2), pp. 185–222 (2000)Google Scholar
  20. 20.
    Weiss, G., Dillenbourg, P.: What is ‘multi‘ in multiagent learning? In: Dillenbourg, P. (ed.) Collaborative Learning. Cognitive and Computational Approaches, pp. 64–80. Pergamon Press (1999)Google Scholar
  21. 21.
    Więch, P., Rybiński, H.: A Novel Approach to Default Reasoning for MAS. In: Szczuka, M., Kryszkiewicz, M., Ramanna, S., Jensen, R., Hu, Q. (eds.) RSCTC 2010. LNCS, vol. 6086, pp. 484–493. Springer, Heidelberg (2010)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Henryk Rybinski
    • 1
  • Dominik Ryżko
    • 1
  • Przemysław Więch
    • 1
  1. 1.Institute of Computer ScienceWarsaw University of TechnologyWarsawPoland

Personalised recommendations