Reducing Interaction Costs for Self-interested Agents

  • Yunqi Zhang
  • Kate Larson
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 13)

Abstract

In many multiagent systems, agents are not able to freely interact with each other or with a centralized mechanism. They may be limited in their interactions by cost or by the inherent structure of the system. Using a combinatorial auction application as motivation, we study the impact of interaction costs and structure on the strategic behaviour of self-interested agents. We present a particular model of costly agent-interaction, and argue that self-interested agents may wish to coordinate their actions with their neighbours so as to reduce their individual costs. We highlight the issues that arise in such a setting, propose a cost-sharing mechanism that agents can use, and discuss group coordination procedures. Experimental work validates our model.

Keywords

Multiagent systems mechanism design communication costs 

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References

  1. 1.
    Archer, A., Feigenbaum, J., Sami, R., Krishnamurthy, A., Shenker, S.: Approximation and collusion in multicast cost sharing. Games and Economic Behavior 47 (2004)Google Scholar
  2. 2.
    Chawla, S., Roughgarden, T., Sundararajan, M.: Optimal cost-sharing mechanisms for steiner forest problems. In: WINE, pp. 112–123 (2006)Google Scholar
  3. 3.
    Graham, D., Marshall, R.: Collusive bidder behavior at single-object second-price and English auctions. Journal of Political Economy 95(6), 1217–1239 (1987)CrossRefGoogle Scholar
  4. 4.
    Li, C., Chawla, S., Rajan, U., Sycara, K.: Mechanism design for coalition formation and cost sharing in group-buying markets. Electronic Commerce Research and Applications 3, 341–354 (2003)CrossRefGoogle Scholar
  5. 5.
    Li, C., Sycara, K.: Algorithm for combinatorial coalition formation and payoff in electronic markets. In: Proceedings of the First International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2002), pp. 120–127 (2002)Google Scholar
  6. 6.
    Manisterski, E., David, E., Kraus, S., Jennings, N.R.: Forming efficient agent groups for completing complex tasks. In: 5th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2006), Hakodate, Japan, pp. 834–841 (2006)Google Scholar
  7. 7.
    Moulin, H., Shenker, S.: Strategyproof sharing of submodular costs: Budget balance versus efficiency. Economic Theory 18, 511–533 (2001)MATHCrossRefMathSciNetGoogle Scholar
  8. 8.
    Padhy, P., Dash, R.K., Martinez, K., Jennings, N.R.: A utility-based sensing and communication model for a glacial sensor network. In: 5th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2006), Hakodate, Japan, pp. 1353–1360 (2006)Google Scholar
  9. 9.
    Sarne, D., Kraus, S.: The Search for Coalition Formation in Costly Environments. In: Klusch, M., Omicini, A., Ossowski, S., Laamanen, H. (eds.) CIA 2003. LNCS (LNAI), vol. 2782. Springer, Heidelberg (2003)Google Scholar
  10. 10.
    Yamamoto, J., Sycara, K.: A stable and efficient buyer coalition formation scheme for e-marketplaces. In: The Proc. of the 5th International Conference on Autonomous Agents (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Yunqi Zhang
    • 1
  • Kate Larson
    • 1
  1. 1.Cheriton School of Computer ScienceUniversity of WaterlooWaterlooCanada

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