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
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