Journal of Korea Game Society (한국게임학회 논문지)

Korea Game Society (한국게임학회)
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Comparison of LDA and PCA for Korean Pro Go Player's Opening Recognition

한국 프로바둑기사 포석 인식을 위한 선형판별분석과 주성분분석 비교

  • Lee, Byung-Doo (Dept. of Baduk Studies, Division of Sports Science, Sehan University)
  • 이병두 (세한대학교 체육학부 바둑학과)
  • Received : 2013.07.12
  • Accepted : 2013.07.31
  • Published : 2013.08.20
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Abstract

The game of Go, which is originated at least more than 2,500 years ago, is one of the oldest board games in the world. So far the theoretical studies concerning to the Go openings are still insufficient. We applied traditional LDA algorithm to recognize a pro player's opening to a class obtained from the training openings. Both class-independent LDA and class-dependent LDA methods are conducted with the Go game records of the Korean top 10 professional Go players. Experimental result shows that the average recognition rate of class-independent LDA is 14% and class-dependent LDA 12%, respectively. Our research result also shows that in contrary to our common sense the algorithm based on PCA outperforms the algorithm based on LDA and reveals the new fact that the Euclidean distance metric method rarely does not inferior to LDA.

적어도 2,500년 전에 기원된 바둑은 세상에서 가장 오래된 보드 게임 중의 하나이다. 아직까지 포석 바둑에 대한 이론적 연구는 여전히 미흡하다. 본 연구는 특정 프로기사의 포석을 갖고 훈련용 포석으로부터 얻어낸 클래스로의 인식을 위해 전통적인 선형판별분석 알고리즘을 적용하였다. 상위 10위권 한국 프로기사의 포석을 갖고 클래스-독립 선형판별분석과 클래스-종속 선형판별분석을 수행하였다. 실험 결과 클래스-독립 LDA는 평균 14%의 인식률을, 클래스-종속 LDA는 평균 12%의 인식률을 각각 보였다. 또한 연구 결과 일반적인 상식과 달리 PCA가 LDA보다 더 우월하고, 유클리디언 거리 측정 방식이 결코 LDA보다 뒤지지 않는다는 새로운 사실이 밝혀졌다.

Keywords

References

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Cited by

  1. Monte-Carlo Tree Search Applied to the Game of Tic-Tac-Toe vol.14, pp.3, 2014, https://doi.org/10.7583/JKGS.2014.14.3.47