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Exceeding the Efficiency of Distributed Approximate Algorithms Enabling by the Multiplexing Method

  • Yasuki Iizuka
  • Kayo Iizuka
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6883)

Abstract

Distributed constraint optimization problems have attracted attention as a method for resolving distribution problems in multiagent environments. In this paper, the authors propose a multiplex method aiming to improve the efficiency of a distributed nondeterministic approximate algorithm for distributed constraint optimization problems. Since much of the calculation time is used to transmit messages, improving efficiency using a multiplex calculation of distributed approximate algorithms might be feasible on the presupposition that the calculation time of each node or a small change in message length has no direct impact. The authors conducted a theoretical analysis of efforts to improve efficiency using a multiplex calculation of distributed approximate algorithms using extreme value theory and verifying with an experiment of a simple algorithm. A significant reduction in calculation time and improvement in the quality of the solution was ascertained, as a result of the experiment.

Keywords

Multiagent System Approximate Algorithm Message Length Multiplex Method Depth First Search Tree 
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 2011

Authors and Affiliations

  • Yasuki Iizuka
    • 1
  • Kayo Iizuka
    • 2
  1. 1.School of ScienceTokai UniversityKanagawaJapan
  2. 2.School of Network and InformationSenshu UniversityKanagawaJapan

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