Selecting the Best Player Formation for Corner-Kick Situations Based on Bayes' Estimation
Abstract
In the domain of the Soccer simulation 2D league of the RoboCup project, 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.
Keywords
Cite
@article{arxiv.1606.01015,
title = {Selecting the Best Player Formation for Corner-Kick Situations Based on Bayes' Estimation},
author = {Jordan Henrio and Thomas Henn and Tomoharu Nakashima and Hidehisa Akiyama},
journal= {arXiv preprint arXiv:1606.01015},
year = {2016}
}
Comments
12 pages, 7 figures, RoboCup Symposium 2016