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Research breakthrough · curated entry

AlphaGo appears in Nature

Mastering the game of Go with deep neural networks and tree search

Date
January 27, 2016
Category
Research breakthrough
Organization / Model
Google DeepMind
Evidence
1 source · 1 evidence family

DeepMind published AlphaGo in Nature, combining deep neural networks, Monte Carlo tree search and reinforcement learning. The paper gave the complete method behind beating a professional Go player.

Curator's note: Cross-checked against the Nature article page.

Curated sources · 1

  1. Original paper · Nature2016-01-27

    Mastering the game of Go with deep neural networks and tree search

    nature.com

Cite this page

This page is a curated static snapshot and can be cited directly. Preferred format GB/T 7714—2025 (electronic resource [EB/OL]); the other 5 styles open below, together with the machine-readable files.

GB/T 7714—2025 (electronic resource [EB/OL])

AI 纪年. AlphaGo 登上《Nature》，深度学习进入围棋[EB/OL]. (2016-01-27)[2026-11-03]. https://aihist.net/e/alphago-2016.html.

APA 7 · American Psychological Association

AI 纪年. (2016, January 27). AlphaGo 登上《Nature》，深度学习进入围棋 [Web page]. https://aihist.net/e/alphago-2016.html

MLA 9 · Modern Language Association

"AlphaGo 登上《Nature》，深度学习进入围棋." AI 纪年, 27 Jan. 2016, aihist.net/e/alphago-2016.html. Accessed 3 Nov. 2026.

Chicago 17 · notes-bibliography

AI 纪年. "AlphaGo 登上《Nature》，深度学习进入围棋." Published Jan. 27, 2016. Accessed Nov. 3, 2026. https://aihist.net/e/alphago-2016.html.

IEEE · citation-reference list

"AlphaGo 登上《Nature》，深度学习进入围棋," AI 纪年, 27 Jan. 2016. [Online]. Available: https://aihist.net/e/alphago-2016.html. [Accessed: 3 Nov. 2026].

ACM · author-date variant

AI 纪年. January 27, 2016. AlphaGo 登上《Nature》，深度学习进入围棋. Retrieved November 3, 2026 from https://aihist.net/e/alphago-2016.html.

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