AlphaGo Zero是谷歌下属公司Deepmind的新版程序。从空白状态学起,在无任何人类输入的条件下,AlphaGo Zero能够迅速自学围棋,并以100:0的战绩击败“前辈”。 2017年10月19日凌晨,在国际学术期刊《自然》(Nature)上发表的一篇研究论文中,谷歌下属公司Deepmind报告新版程序AlphaGo Zero:从空白状态学起,在无任何人类输入的条件下,它能够迅速自学围棋,并以100:0的战绩击败“前辈”。Deepmind的论文一发表,TPU的销量就可能要大增了。其100:0战绩有“造”真嫌疑。


We introduce OLIVAW, an AI Othello player adopting the design principles of the famous AlphaGo series. The main motivation behind OLIVAW was to attain exceptional competence in a non-trivial board game at a tiny fraction of the cost of its illustrious predecessors. In this paper, we show how the AlphaGo Zero's paradigm can be successfully applied to the popular game of Othello using only commodity hardware and free cloud services. While being simpler than Chess or Go, Othello maintains a considerable search space and difficulty in evaluating board positions. To achieve this result, OLIVAW implements some improvements inspired by recent works to accelerate the standard AlphaGo Zero learning process. The main modification implies doubling the positions collected per game during the training phase, by including also positions not played but largely explored by the agent. We tested the strength of OLIVAW in three different ways: by pitting it against Edax, the strongest open-source Othello engine, by playing anonymous games on the web platform OthelloQuest, and finally in two in-person matches against top-notch human players: a national champion and a former world champion.