Implicit Coordination in a Network of Social Drivers: The Role of Information in a Commuting Scenario

  • Ana L. C. Bazzan
  • Manuel Fehler
  • Franziska Klügl
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3898)


One of the major research directions in multi-agent systems is dedicated to learning how to coordinate and whether individual agents’ decisions can lead to globally optimal or at least acceptable solutions. Our long term goal is to study the effect of several types of information to guide the decision process of the individual agents. This present paper addresses simulation of agents’ decision-making regarding route choice, and the role of an information component. This information can be provided by group colleagues, by acquaintances from other groups (small-world), or by route guidance. Besides, we study the role of agents lying about their choices. We compare these scenarios, concluding that information (from some kind of source) is beneficial in general: lying helps only to a certain extent, and route guidance is the best type of information.


Multiagent System Main Route Route Choice Good Route Route Guidance 
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.


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  1. 1.
    Arthur, B.: Inductive reasoning, bounded rationality and the bar problem. Technical Report 94–03–014, Santa Fe Institute (1994)Google Scholar
  2. 2.
    Bazzan, A.L.C., Bordini, R.H., Andriotti, G., Viccari, R., Wahle, J.: Wayward agents in a commuting scenario (personalities in the minotity game). In: Proc. of the Int. Conf. on Multi-Agent Systems (ICMAS). IEEE Computer Science, Los Alamitos (2000)Google Scholar
  3. 3.
    Bazzan, A.L.C., Cavalheiro, A.P.: Influence of social attachment in a small-world network of agents playing the iterated prisoners dilemma. In: Parsons, S., Gmytrasiewicz, P. (eds.) 5th Workshop of Game Theoretic and Decision Theoretic Agents, held together with AAMAS 2003, July 2003, pp. 17–24 (2003)Google Scholar
  4. 4.
    Bazzan, A.L.C., Junges, R.: Congestion tolls as utility alignment between agent and system optimum. In: Proceedings of the Fifth Int. Joint Conference on Autonomous Agents and Multiagent Systems, submitted to AAMAS (2006)Google Scholar
  5. 5.
    Challet, D., Zhang, Y.C.: Emergence of cooperation and organization in an evolutionary game. Physica A 246, 407–418 (1997)CrossRefGoogle Scholar
  6. 6.
    Klügl, F., Bazzan, A.L.C.: Route decision behaviour in a commuting scenario. Journal of Artificial Societies and Social Simulation 7(1) (2004)Google Scholar
  7. 7.
    Klügl, F., Bazzan, A.L.C., Wahle, J.: Selection of information types based on personal utility - a testbed for traffic information markets. In: Proceedings of the Second International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), Melbourne, Australia, pp. 377–384. ACM Press, New York (2003)CrossRefGoogle Scholar
  8. 8.
    Milgram, S.: The small world problem. Psychol. Today 2 (1967)Google Scholar
  9. 9.
    Wardrop, J.G.: Some theoretical aspects of road traffic research. In: Proceedings of the Institute of Civil Engineers, vol. 2, pp. 325–378 (1952)Google Scholar
  10. 10.
    Watts, D.J., Strogatz, S.H.: Collective dynamics of ‘small-world’ networks. Nature 393(6684), 397–498 (1998)CrossRefMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ana L. C. Bazzan
    • 1
  • Manuel Fehler
    • 2
  • Franziska Klügl
    • 2
  1. 1.Instituto de Informática, UFRGSBrazil
  2. 2.Dep. of Artificial IntelligenceUniversity of WürzburgWürzburgGermany

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