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Multi-agent Positioning Mechanism in the Dynamic Environment

  • Hidehisa Akiyama
  • Itsuki Noda
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5001)

Abstract

In this paper, we propose a novel agent positioning mechanism for the dynamic environments. In many problems of the real-world multi-agent/robot domain, a position of each agent is an important factor to affect agents’ performance. Because the real-world problem is generally dynamic, a suitable positions for each agent should be determined according to the current status of the environment. We formalize this issue as a map from a focal point like a ball position in a soccer field to a desirable positioning of each player agent, and propose a method to approximate the map using Delaunay Triangulation. This method is simple, fast and accurate, so that it can be implemented for real-time and scalable problems like RoboCup Soccer. The performance of the method is evaluated in RoboCup Soccer Simulation environment compared with other function approximation method like Normalized Gaussian Network. The result of the evaluation tells us that the proposal method is robust to uneven sample distribution so that we can easily to maintain the mapping.

Keywords

Training Data Voronoi Diagram Delaunay Triangulation Proposal Method Ball Position 
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

  • Hidehisa Akiyama
    • 1
  • Itsuki Noda
    • 1
  1. 1.Information Technology Research Institute, National Institute of Advanced Industrial Science and Technology Japan

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