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.
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Akiyama, H., Noda, I. (2008). Multi-agent Positioning Mechanism in the Dynamic Environment. In: Visser, U., Ribeiro, F., Ohashi, T., Dellaert, F. (eds) RoboCup 2007: Robot Soccer World Cup XI. RoboCup 2007. Lecture Notes in Computer Science(), vol 5001. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68847-1_38
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DOI: https://doi.org/10.1007/978-3-540-68847-1_38
Publisher Name: Springer, Berlin, Heidelberg
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