首页> 外文期刊>ICGA journal >Computer chess: From idea to DeepMind1
【24h】

Computer chess: From idea to DeepMind1

机译:电脑象棋:从构想到DeepMind1

获取原文
获取原文并翻译 | 示例
           

摘要

Computer chess has stimulated human imagination over some two hundred and fifty years. In 1769 Baron Wolfgang von Kempelen promised Empress Maria Theresia in public: "I will invent a machine for a more compelling spectacle [than the magnetism tricks by Pelletier] within half a year."The idea of an intelligent chess machine was born. In 1770 the first demonstration was given.The real development of artificial intelligence (AI) began in 1950 and contains many well-known names, such as Turing and Shannon. One of the first AI research areas was chess. In 1997, a high point was to be reported: world champion Gary Kasparov had been defeated by Deep Blue. The techniques used included searching, knowledge representation, parallelism, and distributed systems. Adaptivity, machine learning and the recently developed deep learning mechanism were only later on added to the computer chess research techniques.The major breakthrough for games in general (including chess) took place in 2017 when (1) the AlphaGo Zero program defeated the world championship program AlphaGo by 100-0 and (2) the technique of deep learning also proved applicable to chess. In the autumn of 2017, the Stockfish program was beaten by AlphaZero by 28-0 (with 72 draws, resulting in a 64-36 victory). However, the end of the disruptive advance is not yet in reach. In fact, we have just started. The next milestone will be to determine the theoretical game value of chess (won, draw, or lost). This achievement will certainly be followed by other surprising developments.
机译:大约250年以来,计算机象棋激发了人们的想象力。 1769年,沃尔夫冈·冯·肯佩伦男爵(Wolfgang von Kempelen)向公众许诺玛丽亚·特蕾莎皇后(Empress Maria Theresia):“我将在半年内发明一种比佩勒帖(Pelletier)的磁像戏更吸引人的眼镜。” 1770年进行了第一次演示.1950年,人工智能(AI)的真正发展开始了,其中包含许多著名的名称,例如图灵(Turing)和香农(Shannon)。国际象棋是最早的AI研究领域之一。 1997年,有一个高峰要报道:世界冠军加里·卡斯帕罗夫(Gary Kasparov)被深蓝击败。使用的技术包括搜索,知识表示,并行性和分布式系统。适应性,机器学习和最近开发的深度学习机制只是后来添加到计算机国际象棋研究技术中的.2017年,当(1)AlphaGo Zero程序击败世界冠军时,一般游戏(包括国际象棋)取得了重大突破。 100-0的AlphaGo程序和(2)深度学习技术也被证明适用于国际象棋。在2017年秋天,Stockfish计划被AlphaZero以28-0击败(72次抽签,以64-36获胜)。但是,破坏性进展的终结尚未到来。实际上,我们才刚刚开始。下一个里程碑将是确定国际象棋的理论游戏价值(赢,输或输)。当然,这一成就将伴随其他令人惊讶的发展。

著录项

  • 来源
    《ICGA journal》 |2018年第3期|160-176|共17页
  • 作者

    van den Herik H. Jaap;

  • 作者单位

    Leiden Univ, Leiden Ctr Data Sci, Leiden, Netherlands;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号