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游戏ai 机器学习_不仅仅是游戏:通过人工智能和机器学习掌握麻将

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游戏ai 机器学习

Microsoft researchers have developed an artificial intelligence (AI) system that has taught itself the intricacies of Mahjong and can now match the skills of some of the world’s top players.

微软的研究人员已经开发了一种人工智能(AI)系统,该系统可以自学麻将的复杂性,现在可以与一些世界顶级玩家的技能相提并论。

The complex board game of chance, bluff, and strategy was invented in China thousands of years ago and remains a passionate pastime for millions of Asians today, with many dedicated competitors playing online.

几千年前在中国发明了复杂的机会,虚张声势和战略棋盘游戏,如今,对于成千上万的亚洲人来说,它仍然是一种充满激情的消遣,许多专注的竞争对手都在网上玩。

Computers have learned to play Chess and another ancient Chinese game, Go, amid much fanfare in the past. But scientists at Microsoft Research (MSR) Asia see their achievement as far more than just a case of technology mastering yet another game.

在过去倍受赞誉的情况下,计算机已经学会了下国际象棋和另一种古老的中国游戏Go。 但是, 亚洲微软研究院(MSR)的科学家认为,他们的成就远不止是掌握另一项技术的案例。

The researchers – who named their system Super Phoenix, or Suphx for short – developed a series of AI algorithmic breakthroughs to navigate the uncertain nature of Mahjong. With more work, these could potentially be applied in real situations to solve problems thrown up by unknown factors and random events.

研究人员将系统命名为Super Phoenix(简称Suphx),他们开发了一系列AI算法突破,以应对麻将的不确定性。 通过更多的工作,这些可能会被应用于实际情况中,以解决未知因素和随机事件引发的问题。

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«For as long as researchers have studied AI, they have worked to build agents capable of accomplishing game missions,» says Dr. Hsiao-Wuen Hon, Corporate Vice President, Microsoft Asia Pacific R&D Group and MSR Asia.

微软亚太研发集团和MSR亚洲公司副总裁Hsiao-Wuen Hon博士说:“只要研究人员研究了AI,他们就一直致力于建立能够完成游戏任务的代理人。”

The MSR Asia team designed Suphx to self-learn Mahjong’s strategies, tactics, and subtleties through the experience of playing against thousands of people on Tenhou – a Japan-based global online Mahjong competition platform with more than 300,000 members.

MSR亚洲团队设计了Suphx,以通过在Tenhou(与日本超过30万会员的日本全球在线在线麻将比赛平台)上与数千人进行比赛的经验中,自学麻将的策略,策略和技巧。

With constant machine learning, Suphx went from being a novice to an expert after more than 5,000 games over four months. The more it played, the more it learned at an ever-increasing pace.

通过不断的机器学习,Suphx在四个月的时间里玩了超过5,000场游戏之后,从新手变成了专家。 播放的越多,就越以不断增加的速度学习到更多。

It has now honed its own playing style and can balance attack and defense moves, strategically weigh short-term losses against long-term gains, and make quick hand calculations and decisions with unclear information.

现在,它已经磨练了自己的打法,可以在进攻和防守动作之间取得平衡,从战略上权衡短期损失与长期收益之间的关系,并利用不清楚的信息快速进行手工计算和决策。

麻将AI研究可以突破AI技术的边界,解决复杂的现实生活中的问题。 (Mahjong AI research can push the boundaries of AI technologies to solve complex real-life problems.)

Suphx has become the first AI system to compete at Tenhou’s prestigious  «10th dan» ranking – something that just 180 people have ever done. Only a handful of professionals now play at a higher level in a private room for human players only.

Suphx已成为第一个在Tenhou享有声望的“第10名”排名中竞争的AI系统-只有180人曾做过。 现在只有少数专业人士在私人房间里供人类玩家玩的更高级别的游戏。

Mahjong is played socially and professionally across East and Southeast Asia and was recently featured in the Hollywood movie, «Crazy Rich Asians.»

麻将在整个东亚和东南亚均具有社交性和职业性,最近在好莱坞电影《疯狂的富裕亚洲人》中出演。

It is very different from Chess and Go, which are «perfect information games» in game theory parlance – as both allow players to see everything on a board that can impact the outcome.

这与Chess和Go完全不同,后者是博弈论中的“完美信息游戏” ,因为两者都允许玩家看到可能影响结果的棋盘上的所有内容。

Mahjong is an «imperfect information game» because many factors are unknown. For instance, players must account for their opponents’ unseen tiles. This can lead to bluffs and unpredictable outcomes as they decide what to discard and whether to meld or fold.

麻将游戏是一种“不完美的信息游戏”,因为许多因素尚不清楚。 例如,玩家必须考虑对手看不见的牌。 这可能会导致虚张声势和不可预测的结果,因为它们决定要丢弃什么以及是否融合或折叠。

«Mahjong is more complex than other board games. So playing becomes an art as well as a science,» says Dr. Hon. «Good Mahjong players rely on a combination of observation, intuition, strategy, calculation, and chance that presents unique challenges for an AI system.»

«麻将比其他棋盘游戏要复杂得多。 因此,演奏既是一门艺术,也是一门科学,»Hon博士说。 «优秀的麻将选手依靠观察,直觉,策略,计算和机会的结合,为AI系统带来了独特的挑战。»

翻译自: https://habr.com/en/company/microsoft/blog/469039/

游戏ai 机器学习

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