Evolving Neural Controllers Using GA for Warcraft 3-Real Time Strategy Game
Chang Kee Tong, Chin Kim On, Jason Teo, Aroland M’conie Jilui Kiring · 2011
This paper presents the research results found for the utilization of a Genetic Algorithm (GA) technique in evolving a set of Artificial Neural Networks (ANNs) weights which functions as controller in deciding what type of unit that should be spawned for winning against the opponent in a RTS game called War craft 3 (custom map). The elitism concept is applied during the optimization processes in order to avoid losing good solutions. The experimentation results show clearly a group of mixed randomized opponent can be defeated by the generated AI army. Hence, it is proof that GA is capable to act as a tuning technique in generating the required controllers in RTS game. Furthermore, the neural controllers generated are able to decide the best group of army used in defeating the opponent.