Earticle

초록

영어

The game of Go represents a major challenge for artificial as well as human intelligences due to its profound complexity. Although computer programs capable of playing Go have existed for decades, the period from 2015 to 2025 has marked a turning point, with these systems achieving—and even exceeding—professional human performance. A notable shift in gameplay strategy emerged around 2016, driven by the adoption of unconventional yet effective moves demonstrated by AI programs, challenging previous conventions of preferred moves. Nowadays, the process of learning Go has evolved from traditional knowledge transfer, based on centuries of established conventions regarding strategy, positional judgement and move value to modern trends developed by AI playing style, lacking the explanatory heuristics inherent in both human style of playing and oral tradition. Facing this new challenge, we rely on our curiosity to understand our opponents’ moves beyond technological and language barriers as we continue to explore the mysterious depths of this timeless game.

목차

Abstract
I. Introduction
II. Related Work
1. Literature
2. New Analysis
III. Methodology
1. Pattern Definition
2. Datasets
3. Pattern Acquisition Algorithm
4. Statistical Analysis
Ⅳ. Findings
1. Change in Frequency of Patterns in Professional Games
2. Evolution of Go Strategies
V. Discussion
VI. Conclusion
VII. Acknowledgements
References

키워드

저자

• Ángel Alberto Sesma González [ Tecnológico de Monterrey (ITESM) Monterrey, MX ]
• Leonardo Jiménez Martínez [ Universidad Autónoma de México (UNAM) Ciudad de México, MX ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  바둑학연구 [Journal of Go Studies]

• 간기

  반년간

• pISSN

  1738-3730

• 수록기간

  2004~2025

• 십진분류

  KDC 691 DDC 794