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Constant Price of Anarchy in Network Creation Games via Public Service Advertising

  • Erik D. Demaine
  • Morteza Zadimoghaddam
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6516)

Abstract

Network creation games have been studied in many different settings recently. These games are motivated by social networks in which selfish agents want to construct a connection graph among themselves. Each node wants to minimize its average or maximum distance to the others, without paying much to construct the network. Many generalizations have been considered, including non-uniform interests between nodes, general graphs of allowable edges, bounded budget agents, etc. In all of these settings, there is no known constant bound on the price of anarchy. In fact, in many cases, the price of anarchy can be very large, namely, a constant power of the number of agents. This means that we have no control on the behavior of network when agents act selfishly. On the other hand, the price of stability in all these models is constant, which means that there is chance that agents act selfishly and we end up with a reasonable social cost.

In this paper, we show how to use an advertising campaign (as introduced in SODA 2009 [2]) to find such efficient equilibria. More formally, we present advertising strategies such that, if an α fraction of the agents agree to cooperate in the campaign, the social cost would be at most O(1 / α) times the optimum cost. This is the first constant bound on the price of anarchy that interestingly can be adapted to different settings. We also generalize our method to work in cases that α is not known in advance. Also, we do not need to assume that the cooperating agents spend all their budget in the campaign; even a small fraction (β fraction) would give us a constant price of anarchy.

Keywords

algorithmic game theory price of anarchy selfish agents 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Erik D. Demaine
    • 1
  • Morteza Zadimoghaddam
    • 1
  1. 1.MIT Computer Science and Artificial Intelligence LaboratoryCambridgeUSA

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