상세정보
학술대회
An Analysis of the Effects of Physical Abilities on RTS Game Outcome Using Machine Learning Approach
- 발행일
- 201910
- 출처
- International Conference on Information and Communication Technology Convergence (ICTC) 2019, pp.929-933
- 협약과제
- 19CS1700, 메타 플레이 인식 기반 지능형 게임 서비스 플랫폼 개발, 양성일
- 초록
- Physical ability in games represents how many actions or multitasks a gamer can do or how fast the gamer can react. In this paper, we characterize physical ability features from Starcraft II data. The proposed win prediction model based on machine learning algorithms evaluates how much features affect a game outcome. Even if features are used only related to physical ability, prediction result shows higher accuracy on a small scale than one with score-related features. Finally, we analyze those features and conclude that although matchmaking rating(MMR) plays primary role to lead a game win, actions per minute and others are also crucial factor to win.
- KSP 제안 키워드
- Machine Learning Algorithms, Machine Learning Approach, RTS games, Small-scale, StarCraft II, Win prediction, model-based, prediction model