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Emerging Properties of Knowledge Sharing Referral Networks: Considerations of Effectiveness and Fairness

  • Priyadarshini Manavalan
  • Munindar P. Singh
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6573)

Abstract

Referral-based peer-to-peer networks have a wide range of applications. They provide a natural framework in which agents can help each other. This paper studies the trade-off between social welfare and fairness in referral networks. The traditional, naive mechanism yields high social welfare but at the cost of some agents—in particular, the “best” ones—being exploited. Autonomous agents would obviously not participate in such networks. An obvious mechanism such as reciprocity improves fairness but substantially lowers welfare. A more general incentive mechanism yields high fairness with only a small loss in welfare. This paper considers substructures of the network that emerge and cause the above outcomes.

Keywords

Social Welfare Relative Performance MultiAgent System Autonomous Agent Agent Exploitation 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Priyadarshini Manavalan
    • 1
  • Munindar P. Singh
    • 1
  1. 1.Department of Computer ScienceNorth Carolina State UniversityRaleighUSA

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