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등록일 : 2015-01-09 12:27:04 | 글번호 : 65657 | 0
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Texas Hold'em poker solved by computer
Card sharks, beware. A new program cannot be beaten at a variety of poker called heads-up limit Texas Hold ’em—at least in a human lifetime—a team of computer scientists reports. Researchers had previously developed unbeatable algorithms for other games such as checkers, but the new work marks the first time scientists have found such an algorithm for—or "solved"—a complex game in which some information about the state of the game (i.e., the cards in his opponent’s hand) remains hidden from the player. The program has yielded insights that could help players improve their game, and the general approach may have real-world usefulness in security and health care applications.

Because of the hidden information and the luck of the draw, the program won't necessarily win every hand, explains computer scientist Michael Bowling of the University of Alberta in Edmonton, Canada, who led the study. But on average the program is so good that a human would have no chance of ever edging ahead of it, even if the two played 60 million hands. So “for all purposes that anyone would ever care about, we’ve solved the game,” Bowling says.


(중략)

Although the study of poker may seem like just fun and games, advances in game theory can have real-world applications in areas such as airport security, coast guard patrols, and health care, in which people must make decisions using the limited information available to them. “I think this is an exciting step that this paper makes, and I think it’s part of a broader development” in such algorithms, says Vincent Conitzer, a computer scientist at Duke University in Durham, North Carolina. “More and more we’re able to apply them directly to real-life games, whether they be poker or these kinds of strategic situations that come up in security.”


http://news.sciencemag.org/math/2015/01/texas-hold-em-poker-solved-computer

세줄요약

1. 텍사스 홀덤 게임에서 반드시 이기는 알고리즘이 개발됨. (태어나서 죽을 때까지 해도 인간이 못 이김)
2. 상대방의 패에 대한 정보가 없는 상태에서, 시뮬레이션과 다른 행동을 할 때 발생하는 "후회" 값이 0에 매우 가까워질 때까지 스스로의 전략을 계속 개량하는 구조.
3. 완전하지 않은 정보를 가지고 최적화된 판단을 할 수 있는 알고리즘이라는 점에서, 현실적으로 다양한 응용이 가능할 것이라 예상됨.

음 사실 홀덤 어떻게 하는지 잘 몰라서 대강 요약했는데, 아무튼 신기하네요.
출처 : 고려대학교 고파스 2025-08-14 02:32:27:


댓글수 3
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댓글 1 익명 2015-01-09 14:23:20
홀덤 하시는 분 계신가요?? :


댓글 2 익명 2015-01-09 16:07:56
헤즈업 리밋만이네요 그래도ㅎㅎ :


댓글 3 익명 2015-01-09 16:10:39
홀덤 오토마우스도 있다고 들은것같은뎅 노리밋이나 여러명앉는테이블에서는 미니멈 바이인해서 타이트하게 하고 번돈은 바로 저금(ㅎㅎ)하는식으로 하는것같던데 헤즈업리밋이면 알고리즘으로 가능할듯 :


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