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Erschienen in:
2017 | OriginalPaper | Buchkapitel
Identifying Rush Strategies Employed in StarCraft II Using Support Vector Machines
verfasst von : Teguh Budianto, Hyunwoo Oh, Yi Ding, Zi Long, Takehito Utsuro
Erschienen in: Entertainment Computing – ICEC 2017
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Abstract
This paper studies the strategies used in StarCraft II, a real-time strategy game (RTS) wherein two sides fight against each other in a battlefield context. We propose an approach which automatically classifies StarCraft II game-log collections into rush and non-rush strategies using a support vector machine (SVM). To achieve this, three types of features are evaluated: (i) the upper bound of variance in time series for the numbers of workers, (ii) the upper bound of the numbers of workers at a specific time, and (iii) the lower bound of the start time for building the second base. Thus, by evaluating these features, we obtain the optimal parameters combinations.