Journal of Korea Game Society (한국게임학회 논문지)

Korea Game Society (한국게임학회)
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Case study of property extraction and utilization model for the game player models

게임 플레이어 모델을 위한 속성 추출과 모델 활용 사례

  • 윤태복 (서일대학교 소프트웨어공학과) ;
  • 양성일 (한국전자통신연구원)
  • Received : 2021.11.17
  • Accepted : 2021.12.13
  • Published : 2021.12.20
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Abstract

As the industry develops, the technology used for games is also being advanced. In particular, AI technology is used to game automation and intelligence. These game player patterns are widely used in online games such as player matchmaking, generation of friendly or hostile NPCs, and balancing of game worlds. This study proposes a model generation method for game players. For model generation, attributes such as hunting, collection, movement, combat, crisis management, production, and interaction were defined, and patterns were extracted and modeled using decision tree method. To evaluate the proposed method, we used the game log of a commercial game and confirmed the meaningful results.

산업의 발전에 따라 게임에 활용되는 기술도 고도화 되고 있다. 특히, 인공지능 기술은 게임로그를 수집하고 분석하여 패턴을 추출하고 게임의 자동화와 지능화를 위하여 활용되고 있다. 이러한 게임 플레이어의 패턴은 온라인 게임에서 플레이어 매칭, 적대적 NPC의 생성, 게임 월드의 밸런싱 등 적용 범위가 넓다. 본 연구에서는 게임 플레이어의 모델 생성 방법을 제안한다. 모델 생성을 위하여 사냥, 수집, 이동, 전투, 위기관리, 제작, 상호작용 등의 속성을 정의하였으며 의사결정나무 방법을 이용하여 패턴을 추출하고 모델링 하였다. 제안하는 방법의 검증을 위하여 상용 게임의 게임 로그를 이용하여 모델링하고 에러율을 확인하였으며 유효한 결과를 확인하였다.

Keywords

Acknowledgement

The present research has been conducted by the Research Grant of Seoil University

References

  1. Korea Creative Content Agency Policy Laboratory, 2018 White paper on Korean games, Korea Creative Content Agency, 2018.
  2. Tae Bok Yoon, Kyo Hyeon Park, Jee Hyong Lee, Keon Myung Lee, "User Adaptive Game Characters Using Decision Trees and FSMs,", Knowledge-based and Intelligent Engineering Systems(KES) AMSTA 2007, 2007.
  3. Jangwoo Kwon, Jang-Hoon Jang, "A Study on Implementation of Intelligent Character for MMORPG using Genetic Algorithm and Neural Networks", Journal of Korea Multimedia Society, Vol 10, No 5, 2007.
  4. JaeYoon Noh, JiHoon Jeon, CheongMok Bae, Kyung-Joong Kim, "Generalized Feature Extraction Method Based on Various Mobile Game Logs for Predicting Gamer Behavior", 2018 Korea Software Society Conference, pp. 818~820, 2018.
  5. Juyoung Kim, Hunjoo Lee, "A Study of Gamebot Detection using Online Game Log Data Analysis", 2013 Korean Information Science Society Korean Proceedings, pp. 680~682, 2013.
  6. Yeonjun Choi, Hunjoo Lee, Yongjun Kim, Seongil Jin, "Detecting Bots in Multiplayer Online Games with Log", The Korea Contents Society, 2013 ICCC Proceedings, Vol. 11, No. 2, 2013.
  7. Tae-Bok Yoon, Jee-Hyong Lee, "A Study of Player Changed-pattern Model for Game Bots Detection in MMORPG", Journal of Korea Game Society, Vol. 11, No. 1, 2011.
  8. Georgios N. Yannakakis, Pieter Spronck, Daniele Loiacono, and Elisabeth Andre, "Player Modeling", Artificial and Computational Intelligence in Games, Vol. 6, 2013.
  9. Danial Hooshyar, Moslem Yousefi, Heuiseok Lim, "Data-Driven Approaches to Game Player Modeling: A Systematic Literature Review", Journal ACM Computing Surveys, Vol. 50, No. 6, 2018.
  10. Hye-Wuk Jung, Sang-Hyun Park, Sung-Woo Bang, Tae-Bok Yoon, Jee-Hyong Lee, "Game Behavior Pattern Modeling for Bots(Auto Program) detection", Journal of Korea Game Society, Vol. 9, No. 5, 2009.
  11. Seon Min Kim, Huy Kang Kim, "A research on improving client based detection feature by using server log analysis in FPS games", Journal of the Korea Institute of Information Security & Cryptology, Vol. 25, No. 6, 2015.
  12. Jung Kyu Park, Mee Lan Han, Huy Kang Kim,"A Study of Cheater Detection in FPS Game by using User Log Analysis", Journal of Korea Game Society, Vol. 15, No. 3, 2015.
  13. Sha Zhao, Yizhi Xu, Zhiling Luo, Jianrong Tao, Shijian Li, Changjie Fan, Gang Pan, "Player Behavior Modeling for Enhancing Role-Playing Game Engagement", IEEE Transactions on Computational Social Systems, Vol. 8, No. 2, April 2021.
  14. Abhijeet Krishnan, Aaron Williams, Chris Martens,"Towards Action Model Learning for Player Modeling", Sixteenth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment Vol. 16 No. 1, 2020.