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围棋人机对弈五十年:第一代围棋AI是中国教授发明

2017-05-24 10:53:07   北京日报

围棋AI之难,难在这项运动本身的多重复杂性“最简单的规则,最复杂的变化”。在AlphaGo及其开发团队DeepMind出现之前,几乎所有研究者都认为在十年内人工智能战胜围棋大师的机会是渺茫的。而在它出现以后,几乎所有人都在惊呼人工智能已破解了围棋这一历史难题,甚至在极短的时间内两次让研究成果上了《自然》杂志的封面。

据AlphaGo官方介绍,AlphaGo采用了一种更加“通用”的人工智能方法,即采用将改进的蒙特卡洛决策树算法与深度神经网络算法相结合的方法构建最终的学习系统。其包括两个部分:策略网络与价值网络。策略网络在当前给定的棋局中,负责预测下一步的走棋,并对下一步走棋的好坏进行打分,策略网络的作用好比“模仿”人类棋手的各种走法,以达到预测的效果。然而仅凭模仿无法击败最顶级的人类高手,AlphaGo又增加了价值网络来判断当前的局面到底对哪一方有利,但围棋程序的局势评估相当困难,只能通过深度学习网络之间自我训练的方法来达到良好的效果。

2016年3月,AlphaGo以4:1战胜世界围棋名将李世石,AlphaGo的实力首次被世人真正认可。AlphaGo 2.0版本的升级亮点是摒弃人类棋谱,即仅通过监督学习和强化学习,再度进化出新的“围棋机器人”。

事实上,除了AlphaGo,现在还有其他围棋AI程序也已被证明达到甚至超过了人类棋手的一流水平,比如腾讯AI Lab(腾讯人工智能实验室)研发的围棋人工智能程序“绝艺”(Fine Art),它在今年首次参加UEC杯计算机围棋大赛,就以11连胜夺得了本届UEC杯冠军,在随后的人机大战中完胜日本先锋棋手一力辽。

AI作为工具,被人类棋手“喂招”不断进化后,它也能“反哺”人类,棋手使用围棋AI开展人机协同,AI为人类棋手“蓄力”,1+1>2的进化成为了新看点。随着数据量的高速增长,AI可以分析总结、自我学习,人则可以通过善用AI、人机协作,开启智慧时代,改变现在以及未来的一切。(作者为《机器人产业》杂志副总编)

(原标题:围棋人机对弈五十年)

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