Role Model Based Mechanism for Norm Emergence in Artificial Agent Societies

  • Bastin Tony Roy Savarimuthu
  • Stephen Cranefield
  • Maryam Purvis
  • Martin Purvis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4870)


In this paper we propose a mechanism for norm emergence based on role models. The mechanism uses the concept of normative advice whereby the role models provide advice to the follower agents. Our mechanism is built using two layers of networks, the social link layer and the leadership layer. The social link network represents how agents are connected to each other. The leadership network represents the network that is formed based on the role played by each agent on the social link network. The two kinds of roles are leaders and followers. We present our findings on how norms emerge on the leadership network when the topology of the social link network changes. The three kinds of social link networks that we have experimented with are fully connected networks, random networks and scale-free networks.


Norm Emergence Role Model Multiagent System Random Network Autonomous Agent 
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.
    Boella, G., Torre, L., Verhagen, H.: Introduction to normative multiagent systems. Computational and Mathematical Organization Theory 12(2–3), 71–79 (2006)CrossRefGoogle Scholar
  2. 2.
    Kittock, J.E.: The impact of locality and authority on emergent conventions: Initial observations. In: Proceedings of the twelfth national conference on Artificial intelligence, American Association for Artificial Intelligence Menlo Park, CA, USA, pp. 420–425 (1994)Google Scholar
  3. 3.
    Habermas, J.: The Theory of Communicative Action: Reason and the Rationalization of Society, vol. 1. Beacon Press (1985)Google Scholar
  4. 4.
    Tuomela, R.: The Importance of Us: A Philosophical Study of Basic Social Notions. Stanford Series in Philosophy, Stanford University Press (1995)Google Scholar
  5. 5.
    Elster, J.: Social norms and economic theory. The Journal of Economic Perspectives 3(4), 99–117 (1989)MathSciNetGoogle Scholar
  6. 6.
    Shoham, Y., Tennenholtz, M.: On social laws for artificial agent societies: Off-line design. Artificial Intelligence 73(1-2), 231–252 (1995)CrossRefGoogle Scholar
  7. 7.
    Boman, M.: Norms in artificial decision making. Artificial Intelligence and Law 7(1), 17–35 (1999)CrossRefMathSciNetGoogle Scholar
  8. 8.
    Conte, R., Falcone, R., Sartor, G.: Agents and norms: How to fill the gap? Artificial Intelligence and Law 7(1), 1–15 (1999)CrossRefGoogle Scholar
  9. 9.
    Castelfranchi, C., Conte, R.: Cognitive and social action. UCL Press, London (1995)Google Scholar
  10. 10.
    López y López, F., Márquez, A.A.: An architecture for autonomous normative agents. In: Fifth Mexican International Conference in Computer Science (ENC 2004), pp. 96–103. IEEE Computer Society Press, Los Alamitos (2004)CrossRefGoogle Scholar
  11. 11.
    Boella, G., van der Torre, L.: An architecture of a normative system: Counts-as conditionals, obligations and permissions. In: Proceedings of the fifth international joint conference on autonomous agents and multiagent systems, AAMAS, pp. 229–231. ACM Press, New York (2006)CrossRefGoogle Scholar
  12. 12.
    García-Camino, A., Rodríguez-Aguilar, J.A., Sierra, C., Vasconcelos, W.: Norm-oriented programming of electronic institutions. In: Proceedings of the fifth international joint conference on autonomous agents and multiagent systems, AAMAS, pp. 670–672. ACM Press, New York (2006)CrossRefGoogle Scholar
  13. 13.
    López y López, F., Luck, M., d’Inverno, M.: Constraining autonomy through norms. In: Proceedings of The First International Joint Conference on autonomous Agents and Multi Agent Systems, AAMAS, pp. 674–681. ACM Press, New York (2002)CrossRefGoogle Scholar
  14. 14.
    Aldewereld, H., Dignum, F., García-Camino, A., Noriega, P., Rodríguez-Aguilar, J.A., Sierra, C.: Operationalisation of norms for usage in electronic institutions. In: Proceedings of The Fifth International Joint Conference on autonomous Agents and Multi Agent Systems, AAMAS, pp. 223–225. ACM Press, New York (2006)CrossRefGoogle Scholar
  15. 15.
    Axelrod, R.: An evolutionary approach to norms. The American Political Science Review 80(4), 1095–1111 (1986)CrossRefGoogle Scholar
  16. 16.
    Fix, J., von Scheve, C., Moldt, D.: Emotion-based norm enforcement and maintenance in multi-agent systems: foundations and petri net modeling. In: Proceedings of the fifth international joint conference on autonomous agents and multiagent systems, AAMAS, pp. 105–107 (2006)Google Scholar
  17. 17.
    Pitt, J.: Digital blush: Towards shame and embarrassment in multi-agent information trading applications. Cognition, Technology and Work 6(1), 23–36 (2004)CrossRefGoogle Scholar
  18. 18.
    Conte, R., Castelfranchi, C.: From conventions to prescriptions - towards an integrated view of norms. Artificial Intelligence and Law 7(4), 323–340 (1999)CrossRefGoogle Scholar
  19. 19.
    Boyd, R., Richerson, P.J.: Culture and the evolutionary process. University of Chicago Press, Chicago (1985)Google Scholar
  20. 20.
    Verhagen, H.: Simulation of the Learning of Norms. Social Science Computer Review 19(3), 296–306 (2001)CrossRefGoogle Scholar
  21. 21.
    Verhagen, H.: Norm Autonomous Agents. PhD thesis, Department of Computer Science, Stockholm University (2000)Google Scholar
  22. 22.
    Opp, K.D.: How do norms emerge? An outline of a theory. Mind and Society 2(1), 101–128 (2001)CrossRefGoogle Scholar
  23. 23.
    Epstein, J.M.: Learning to be thoughtless: Social norms and individual computation. Computational Economics 18(1), 9–24 (2001)zbMATHCrossRefGoogle Scholar
  24. 24.
    Sen, S., Airiau, S.: Emergence of norms through social learning. In: Proceedings of Twentieth International Joint Conference on Artificial Intelligence (IJCAI), Hyderabad, India, pp. 1507–1512. MIT Press, Cambridge (2006)Google Scholar
  25. 25.
    Nakamaru, M., Levin, S.A.: Spread of two linked social norms on complex interaction networks. Journal of Theoretical Biology 230(1), 57–64 (2004)CrossRefMathSciNetGoogle Scholar
  26. 26.
    Pujol, J.M.: Structure in Artificial Societies. PhD thesis, Llenguatges i Sistemes Informátics, Universitat Politénica de Catalunya (2006)Google Scholar
  27. 27.
    Fortunato, S.: Damage spreading and opinion dynamics on scale free networks (2004)Google Scholar
  28. 28.
    Cohen, R., Havlin, S., ben-Avraham, D.: Efficient immunization strategies for computer networks and populations. Physical Review Letters 91, 247–901 (2003)Google Scholar
  29. 29.
    Pujol, J.M., Sangüesa, R., Delgado, J.: Extracting reputation in multi agent systems by means of social network topology. In: Proceedings of the first international joint conference on autonomous agents and multiagent systems, AAMAS, pp. 467–474. ACM Press, New York (2002)CrossRefGoogle Scholar
  30. 30.
    Yu, B., Singh, M.P.: Searching social networks. In: Proceedings of the second international joint conference on autonomous agents and multiagent systems, AAMAS, pp. 65–72. ACM Press, New York (2003)CrossRefGoogle Scholar
  31. 31.
    Erdös, P., Renyi, A.: On random graphs - i. Publicationes Mathematicae Debrecen 6, 290 (1959)MathSciNetzbMATHGoogle Scholar
  32. 32.
    Barabási, A.L., Albert, R.: Emergence of scaling in random networks. Science 286, 509–512 (1999)CrossRefMathSciNetGoogle Scholar
  33. 33.
    Mitchell, M.: Complex systems: Network thinking. Artificial Intelligence 170(18), 1194–1212 (2006)CrossRefMathSciNetGoogle Scholar
  34. 34.
    Gintis, H.: Solving the Puzzle of Prosociality. Rationality and Society 15(2), 155–187 (2003)CrossRefGoogle Scholar
  35. 35.
    Slembeck, T.: Reputations and fairness in bargaining - experimental evidence from a repeated ultimatum game with fixed opponents. Technical report, EconWPA (1999),
  36. 36.
    Albert, R., Barabasi, A.-L.: Statistical mechanics of complex networks. Reviews of Modern Physics 74, 47–97 (2002)CrossRefMathSciNetGoogle Scholar
  37. 37.
    Albert, R., Jeong, H., Barabasi, A.L.: Error and attack tolerance of complex networks. Nature 406(6794), 378–382 (2000)CrossRefGoogle Scholar
  38. 38.
    Bollobás, B., Riordan, O.: The diameter of a scale-free random graph. Combinatorica 24(1), 5–34 (2004)zbMATHCrossRefMathSciNetGoogle Scholar
  39. 39.
    Anghel, M., Toroczkai, Z., Bassler, K.E., Korniss, G.: Competition-driven network dynamics: Emergence of a scale-free leadership structure and collective efficiency. Physical Review Letters 92(5), 587011–587014 (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Bastin Tony Roy Savarimuthu
    • 1
  • Stephen Cranefield
    • 1
  • Maryam Purvis
    • 1
  • Martin Purvis
    • 1
  1. 1.Department of Information ScienceUniversity of OtagoDunedinNew Zealand

Personalised recommendations