Mining RoboCup Log Files to Predict Own and Opponent Action

Maryam Karimi, Marzieh Ahmazadeh


RoboCup is an international research aimed at improving artificial intelligence and robotics. It is a standard issue to get a wide range of technologies together and obtain new achievements. In 2D simulation league, after each game, server saves a log that contains all information about the game. By using data mining techniques knowledge can be discovered from this massive data. In this research we aimed to extract ball and player positions from log files and pre-process this data to specify some information including the action that have been taken place, start point, and involving players, etc. We mined this data to predict own and opponent action using C4.5 algorithm. The result showed that after applying our method the goal scoring was increased 251.39% with 64.13% confidence interval (with alpha = 0.1).


Keywords: RoboCup, data mining, classification, C4.5, log processing

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