6533b831fe1ef96bd1298380
RESEARCH PRODUCT
Behavior Classification with Self-Organizing Maps
Daniel PolaniDaniel PolaniMichael WünstelJürgen PerlThomas Uthmannsubject
Self-organizing mapbusiness.industryComputer scienceArtificial intelligencebusinessCluster analysisMachine learningcomputer.software_genrecomputerMotion (physics)description
We describe a method that applies Self-Organizing Maps for direct clustering of spatio-temporal data. We use the method to evaluate the behavior of RoboCup players. By training the Self-Organizing Map with player data we have the possibility to identify various clusters representing typical agent behavior patterns. Thus we can draw certain conclusions about their tactical behavior, using purely motion data, i.e. logfile information. In addition, we examine the player-ball interaction that give information about the players' technical capabilities.
year | journal | country | edition | language |
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2001-01-01 |