Research and Implementation of Robocode Decision-making System Based on Jess and Machine Learning
Guangqiang Li · Jisuanji fangzhen · 2006
Based on Java Rule Engine and machine learning, a new method to construct Robocode decision-making system was presented. This method developed and maintained the decision-making system by Jess, making the decision-making system more real-time reactive and extendible. At the meantime, this method used machine learning to train tank fighters, enhancing the online adaptive and self-learning ability. To complete the job, a hybrid moving action selector was proposed by an integration of genetic algorithm and production system, and a neural network was chosen to optimize the firing angle of aiming rules. The results in the experiment show the effectiveness of aiming system and moving system.