DocumentCode :
1850019
Title :
Evolving Neural Controllers Using GA for Warcraft 3-Real Time Strategy Game
Author :
Tong, Chang Kee ; On, Chin Kim ; Teo, Jason ; Kiring, Aroland MConie Jilui
Author_Institution :
Sch. of Eng. & Inf. Technol., Univ. Malaysia Sabah, Kota Kinabalu, Malaysia
fYear :
2011
fDate :
27-29 Sept. 2011
Firstpage :
15
Lastpage :
20
Abstract :
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.
Keywords :
artificial intelligence; computer games; control system synthesis; genetic algorithms; neurocontrollers; AI army; GA; RTS game; Warcraft 3-real time strategy game; artificial neural networks; genetic algorithm technique; neural controllers; tuning technique; Artificial intelligence; Artificial neural networks; Games; Genetic algorithms; Humans; MIMICs; Optimization; Artificial Intelligence (AI); Artificial Neural Networks (ANNs); Genetic Algorithm (GA); Real-Time Strategy Game (RTS); Warcraft 3;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bio-Inspired Computing: Theories and Applications (BIC-TA), 2011 Sixth International Conference on
Conference_Location :
Penang
Print_ISBN :
978-1-4577-1092-6
Type :
conf
DOI :
10.1109/BIC-TA.2011.70
Filename :
6046866
Link To Document :
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