Computer chess: From idea to DeepMind¹

Article type: Review Article

Authors: van den Herik, H. Jaap^{; *}

Affiliations: Leiden Centre of Data Science, Universiteit Leiden

Correspondence: [*] Corresponding author. E-mail: [email protected].

Note: [1] This article is an elaboration of my keynote lecture delivered at the 10th International Conference on Computers and Games (CG 2018) in the National Taipei University in Taipei, Taiwan on July 9, 2018.

Abstract: 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.

DOI: 10.3233/ICG-180075

Journal: ICGA Journal, vol. 40, no. 3, pp. 160-176, 2018