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삼목게임에서의 몬테카를로 트리탐색과 신뢰상한 트리탐색간의 경쟁
Competition between MCTS and UCT in the game of Tic-Tac-Toe
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- 발행기관
- 한국컴퓨터게임학회 바로가기
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- 간행물
- 컴퓨터게임및콘텐츠논문지(구 한국컴퓨터게임학회논문지) KCI 등재 바로가기
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- 통권
- 제29권 제1호 (2016.03)바로가기
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- 페이지
- pp.1-6
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- 저자
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- 언어
- 한국어(KOR)
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- URL
- https://www.earticle.net/Article/A301017
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4,000원
원문정보
초록
- 영어
- Go is an extremely complex strategic board game despite its simple rules and is the great challenging classic game for AI due to its enormous search space. The computer program AlphaGo finally defeated Fan Hui, the European Go champion, without handicaps on a full-sized 19 ×19 board in October 2015. Monte-Carlo Tree Search (MCTS) is a widely-used algorithm for game-tree search in game playing. MCTS based on statistical sampling is a best-first tree search technique to evaluate states; UCT which is a variant of MCTS uses the UCB1 formula as selection policy. In this paper, we evaluate the performance of MCTS and UCT playing against each other in the game of Tic-Tac-Toe. The experimental results show that the first player UCT is slightly superior to the second player MCTS (54.3±1.0%), the first player is always advantageous to the second player regardless of the MCTS and UCT players, and the result of each game should be a tie if both players do their best in Tic-Tac-Toe. Go is an extremely complex strategic board game despite its simple rules and is the great challenging classic game for AI due to its enormous search space. The computer program AlphaGo finally defeated Fan Hui, the European Go champion, without handicaps on a full-sized 19 ×19 board in October 2015. Monte-Carlo Tree Search (MCTS) is a widely-used algorithm for game-tree search in game playing. MCTS based on statistical sampling is a best-first tree search technique to evaluate states; UCT which is a variant of MCTS uses the UCB1 formula as selection policy. In this paper, we evaluate the performance of MCTS and UCT playing against each other in the game of Tic-Tac-Toe. The experimental results show that the first player UCT is slightly superior to the second player MCTS (54.3±1.0%), the first player is always advantageous to the second player regardless of the MCTS and UCT players, and the result of each game should be a tie if both players do their best in Tic-Tac-Toe.
목차
ABSTRACT
1. 서론
2. 본론
2.1 몬테카를로 트리탐색
2.2 신뢰상한 트리탐색
3. 실험 결과
4. 결론
참고문헌
키워드
Computer Go Tic-Tac-Toe MCTS Monte-Carlo algorithm UCT Upper Confidence Bounds for Trees Exploration-Exploitation dilemma UCB Upper Confidence Bound저자
간행물 정보
발행기관
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- 발행기관명
- 한국컴퓨터게임학회 [Korean Society for Computer Game]
- 설립연도
- 2002
- 분야
- 공학>컴퓨터학
- 소개
- 1. 게임산업을 활성화 하고, 2. 게임기술과 기술 인력을 양산할 수 있도록 교육기관의 교과과정을 개발하고, 3. 관련기술에 대한 연구발표회, 강연회, 강습회 등을 개최하며, 4. 학회지, 논문지 및 관련 문헌을 발간하고, 5. 게임 기술 개발을 위한 국제화, 표준화 등을 지원하고, 6. 산.학.연.관이 협동할 수 있는 국제적 학술교류 및 협력을 지원하고, 7. 회원 상호간의 공동 이익과 친목을 증진시킨다.
간행물
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- 간행물명
- 컴퓨터게임및콘텐츠논문지(구 한국컴퓨터게임학회논문지) [Journal of Computer Games and Contents]
- 간기
- 월간
- pISSN
- 3091-7409
- eISSN
- 3092-3638
- 수록기간
- 2002~2026
- 등재여부
- KCI 등재
- 십진분류
- KDC 691 DDC 793
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