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2017 | OriginalPaper | Chapter

Selecting the Best Player Formation for Corner-Kick Situations Based on Bayes’ Estimation

Authors : Jordan Henrio, Thomas Henn, Tomoharu Nakashima, Hidehisa Akiyama

Published in: RoboCup 2016: Robot World Cup XX

Publisher: Springer International Publishing

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Abstract

In the domain of RoboCup 2D soccer simulation league, appropriate player positioning against a given opponent team is an important factor of soccer team performance. This work proposes a model which decides the strategy that should be applied regarding a particular opponent team. This task can be realized by applying preliminary a learning phase where the model determines the most effective strategies against clusters of opponent teams. The model determines the best strategies by using sequential Bayes’ estimators. As a first trial of the system, the proposed model is used to determine the association of player formations against opponent teams in the particular situation of corner-kick. The implemented model shows satisfying abilities to compare player formations that are similar to each other in terms of performance and determines the right ranking even by running a decent number of simulation games.

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Metadata
Title
Selecting the Best Player Formation for Corner-Kick Situations Based on Bayes’ Estimation
Authors
Jordan Henrio
Thomas Henn
Tomoharu Nakashima
Hidehisa Akiyama
Copyright Year
2017
DOI
https://doi.org/10.1007/978-3-319-68792-6_36

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