Norms and Learning in Probabilistic Logic-Based Agents

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7393)


This paper proposes a new simulation approach for investigating phenomena such as norm emergence and internalization in large groups of learning agents. We define a probabilistic defeasible logic instantiating Dung’s argumentation framework. Rules of this logic are attached to probabilities and describe the agents’ minds and behaviour. We thus adopt the paradigm of reinforcement learning over this probability distribution to allow agents to adapt to their environment.


Reinforcement Learning Argumentation Framework Probabilistic Rule Pure Theory Social Simulation 
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.
    Andrighetto, G., Campennì, M., Cecconi, F., Conte, R.: The complex loop of norm emergence: A simulation model. In: Simulating Interacting Agents and Social Phenomena. Springer (2010)Google Scholar
  2. 2.
    Andrighetto, G., Villatoro, D., Conte, R.: Norm internalization in artificial societies. AI Commun. 23(4), 325–339 (2010)MathSciNetGoogle Scholar
  3. 3.
    Davidsson, P.: Multi Agent Based Simulation: Beyond Social Simulation. In: Moss, S., Davidsson, P. (eds.) MABS 2000. LNCS (LNAI), vol. 1979, pp. 97–107. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  4. 4.
    Davidsson, P.: Agent based social simulation: A computer science view. J. Artificial Societies and Social Simulation 5(1) (2002)Google Scholar
  5. 5.
    Dung, P.M.: On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artificial Intelligence 77(2), 321–358 (1995)MathSciNetzbMATHCrossRefGoogle Scholar
  6. 6.
    Dung, P.M., Thang, P.M.: Towards (probabilistic) argumentation for jury-based dispute resolution. In: Baroni, P., Cerutti, F., Giacomin, M., Simari, G.R. (eds.) COMMA. Frontiers in Artificial Intelligence and Applications, vol. 216, pp. 171–182. IOS Press (2010)Google Scholar
  7. 7.
    Governatori, G., Rotolo, A., Sartor, G.: Temporalised normative positions in defeasible logic. In: 10th International Conference on Artificial Intelligence and Law, pp. 25–34. ACM Press (2005)Google Scholar
  8. 8.
    Haenni, R.: Probabilistic argumentation. J. Applied Logic 7(2), 155–176 (2009)MathSciNetzbMATHCrossRefGoogle Scholar
  9. 9.
    Prakken, H.: An abstract framework for argumentation with structured arguments. Argument and Computation 1(2), 93–124 (2011)CrossRefGoogle Scholar
  10. 10.
    Riveret, R., Prakken, H., Rotolo, A., Sartor, G.: Heuristics in argumentation: A game theory investigation. In: COMMA, pp. 324–335 (2008)Google Scholar
  11. 11.
    Riveret, R., Rotolo, A., Sartor, G., Prakken, H., Roth, B.: Success chances in argument games: a probabilistic approach to legal disputes. In: Proceeding of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference, pp. 99–108. IOS Press, Amsterdam (2007)Google Scholar
  12. 12.
    Roth, B., Riveret, R., Rotolo, A., Governatori, G.: Strategic argumentation: a game theoretical investigation. In: Proceedings of the 11th International Conference on Artificial Intelligence and Law, ICAIL 2007, pp. 81–90. ACM, New York (2007)Google Scholar
  13. 13.
    Savarimuthu, B.T.R., Cranefield, S.: Norm creation, spreading and emergence: A survey of simulation models of norms in multi-agent systems. Multiagent and Grid Systems 7(1), 21–54 (2011)Google Scholar
  14. 14.
    Shoham, Y., Powers, R., Grenager, T.: If multi-agent learning is the answer, what is the question? Artificial Intelligence 171(7), 365–377 (2007)MathSciNetzbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Department of Electrical and Electronic EngineeringImperial College of Science, Technology and MedicineLondonUK
  2. 2.CIRSFIDUniversity of BolognaItaly
  3. 3.European University InstituteFlorenceItaly

Personalised recommendations