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2015 | OriginalPaper | Buchkapitel

Learning Soccer Drills for the Small Size League of RoboCup

verfasst von : Carlos Quintero, Saith Rodríguez, Katherín Pérez, Jorge López, Eyberth Rojas, Juan Calderón

Erschienen in: RoboCup 2014: Robot World Cup XVIII

Verlag: Springer International Publishing

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Abstract

This paper shows the results of applying machine learning techniques to the problem of predicting soccer plays in the Small Size League of RoboCup. We have modeled the task as a multi-class classification problem by learning the plays of the STOx’s team. For this, we have created a database of observations for this team’s plays and obtained key features that describe the game state during a match. We have shown experimentally, that these features allow two learning classifiers to obtain high prediction accuracies and that most miss-classified observations are found early on the plays.

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Metadaten
Titel
Learning Soccer Drills for the Small Size League of RoboCup
verfasst von
Carlos Quintero
Saith Rodríguez
Katherín Pérez
Jorge López
Eyberth Rojas
Juan Calderón
Copyright-Jahr
2015
DOI
https://doi.org/10.1007/978-3-319-18615-3_32