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A Method to Derive Local Interaction Strategies for Improving Cooperation in Self-Organizing Systems

  • Christopher Auer
  • Patrick Wüchner
  • Hermann de Meer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5343)

Abstract

To achieve a preferred global behavior of self-organizing systems, suitable local interaction strategies have to be found. In general, this is a non-trivial task. In this paper, a general method is proposed that allows to systematically derive local interaction strategies by specifying the preferred global behavior. In addition, the resulting strategies can be evaluated using Markovian analysis. Then, by applying the proposed method exemplarily to the iterated prisoner’s dilemma, we are able to systematically generate a cooperation-fostering strategy which can be shown to behave similar to the “tit for tat with forgiveness” strategy that, under certain circumstances, outperforms the well-known “tit for tat” strategy used, for instance, in BitTorrent peer-to-peer file-sharing networks.

Keywords

Global Knowledge Interaction Strategy Mutual Cooperation Markovian Analysis Global Cooperation 
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 2008

Authors and Affiliations

  • Christopher Auer
    • 1
  • Patrick Wüchner
    • 1
  • Hermann de Meer
    • 1
  1. 1.Faculty of Informatics and MathematicsUniversity of PassauPassauGermany

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