Soccer agents using inductive learning with hand-coded rules
Hisayuki Sasaoka, Shinjiro Muraki, Kenji Araki · 2004
This paper proposes a learning method for rules of soccer agents' actions in RoboCup Soccer. In general, soccer agents need to do high skilled actions in real time and they should have a mechanism to decide the actions. The soccer agents based on our method refer to some types of rules in order that they go into highly skilled actions. One type of them is the rules that are Hand-coded rules. Another type is the rules that are acquired using inductive learning and they are acquired from examples of actions, automatically. We describe the basic idea for them and indicate examples of rules.