Strategy Analysis by Self-Organizing Map Using player’s positioning

Abstract

In the soccer games, the behavior selection of each player changes depend on the positional relationship of the ball and the every player’s position on the field. The player closest to the ball near the opponent team’s goal aims at a shot, and the farthest player waits at a position where he can return at any time to his own goal to protect. Currently most of RoboCup soccer teams keep the same strategy during the game so that the result of game depends on the ability of each player like speed of robot, quality of localization, obstacle avoidance and ball handling. Next issue for the robot intelligence is collaborated team behavior and strategy. The autonomous soccer robots are required to behave cooperatively and make decision using environment and game situation. In this research, the team strategy is analyzed based on the positions of human player using Self-Organizing Map (SOM).