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View all- Lee CAhn C(2021)Feature Extraction for StarCraft II League PredictionElectronics10.3390/electronics1008090910:8(909)Online publication date: 11-Apr-2021
Extracting Control Features to Predict a Player’s League in StarCraft II
Pages 1 - 3
Abstract
The players are divided into seven leagues depending on their skill in StarCraft II. Since it is most ideal for players with similar skills to play games, it is important to be included in the right league. This paper proposes a method to predict a player’s league. Our proposed method is extracting control features from the replay, and introduce a useful feature that is not well known. We use a Random Forest for verifying the importance of features.
References
[1]
T. Avontuur, P. Spronck, and M. Zaanen. 2013. Player Skill Modeling in Starcraft II. In AIIDE.
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S. Liu, C. Ballinger, and S.J. Louis. 2013. Player identification from RTS game replays. 28th International Conference on Computers and Their Applications 2013, CATA 2013 (01 2013), 313–318.
[3]
Fernando Palero, Cristian Ramirez-Atencia, and David Camacho. 2015. Online Gamers Classification Using K-means. In Intelligent Distributed Computing VIII, David Camacho, Lars Braubach, Salvatore Venticinque, and Costin Badica (Eds.). Springer International Publishing, Cham, 201–208.
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Rodrigo Vicencio-Moreira, Regan Mandryk, and Carl Gutwin. 2015. Now You Can Compete With Anyone: Balancing Players of Different Skill Levels in a First-Person Shooter Game. In CHI’15: Proceedings of the 2015 CHI international conference on Human factors in computing systems. Seoul, Korea, 2255–2264. Honourable Mention Award given to top 5% of submissions.
[5]
Oriol Vinyals, I. Babuschkin, W. Czarnecki, 2019. Grandmaster level in StarCraft II using multi-agent reinforcement learning. Nature (2019), 1–5.
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- Extracting Control Features to Predict a Player’s League in StarCraft II
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Published In
September 2020
491 pages
ISBN:9781450389259
DOI:10.1145/3426020
Copyright © 2020 ACM.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 04 November 2021
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- Short-paper
- Research
- Refereed limited
Funding Sources
- National Research Foundation ofKorea (NRF) grant
Conference
SMA 2020
SMA 2020: The 9th International Conference on Smart Media and Applications
September 17 - 19, 2020
Jeju, Republic of Korea
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View all- Lee CAhn C(2021)Feature Extraction for StarCraft II League PredictionElectronics10.3390/electronics1008090910:8(909)Online publication date: 11-Apr-2021
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