Evaluation-function modeling with neural networks for RoboCup soccer

Abstract

The quality of decision making by a RoboCup soccer agent depends on a path-planning and an evaluation function of a soccer field. In this paper, we employ a five-layered neural network as the evaluation function. We examine the performance of the soccer agents with various features (ball coordinates and opponents’ positions). We found that the neural network model helps soccer agents to imitate an expert team's decision making.