Self-Evaluation of RTS Troop's performance

Chin, Kim On and Chang, Kee Tong and Rayner Alfred, and Wang Cheng, and Tan, Tse Guan (2015) Self-Evaluation of RTS Troop's performance. Journal of Teknologi. pp. 119-126. ISSN 2180–3722


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This paper demonstrates the research results obtained from a comparison of Evolutionary Programming (EP) and hybrid Differential Evolution (DE) and Feed Forward Neural Network (FFNN) algorithms in the Real Time Strategy (RTS) computer game, namely Warcraft III. The main aims of this research are to: test the feasibility of implementing EP and hybrid DE into RTS game, compare the performances of EP and hybrid DE, and generate gaming RTS controllers autonomously, an issue primarily of reinforcement/troops balancing. This micromanagement issue has been overlooked since last decade. Experimental results demonstrate success with all aims: both EP and hybrid DE could be implemented into the Warcraft III platform, and both algorithms used able to generate optimal solutions.

Item Type: Article
Uncontrolled Keywords: RTS games,evolutionary computing,evolutionary programming, differential evolution, feed-forward neural network
Subjects: Q Science > QA Mathematics
Divisions: FACULTY > Faculty of Engineering
Depositing User: Unnamed user with email
Date Deposited: 05 Jan 2017 07:21
Last Modified: 23 Oct 2017 08:37

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