AlphaGo

E39541

Go-playing program artificial intelligence system computer program

AlphaGo is an artificial intelligence program developed by DeepMind that became famous for defeating world champion Go players using deep neural networks and reinforcement learning.

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All labels observed (10)

Label	Occurrences
AlphaGo canonical	14
AlphaGo Master	3
AlphaGo Lee	2
AlphaGo Fan	1
AlphaGo development team	1
AlphaGo match against Lee Sedol	1
AlphaGo project	1
AlphaGo vs Fan Hui match	1
AlphaGo–Fan Hui five-game match in 2015	1
Mastering the game of Go with deep neural networks and tree search	1

Statements (53)

Predicate	Object
instanceOf	Go-playing program ⓘ artificial intelligence system ⓘ computer program ⓘ
alsoKnownAs	AlphaGo Fan ⓘ AlphaGo ⓘ surface form: AlphaGo Lee AlphaGo ⓘ surface form: AlphaGo Master
basedOn	deep learning ⓘ machine learning ⓘ policy networks ⓘ value networks ⓘ
boardGame	Go ⓘ
countryOfOrigin	United Kingdom ⓘ
developer	DeepMind ⓘ DeepMind ⓘ surface form: Google DeepMind
field	artificial intelligence research ⓘ computer Go ⓘ
firstReleaseYear	2015 ⓘ
genre	board game AI ⓘ
governingBodyInMatch	Chinese Weiqi Association ⓘ Korea Baduk Association ⓘ
inspired	AlphaZero ⓘ surface form: AlphaGo Zero AlphaZero ⓘ MuZero ⓘ
matchDate	2015-10 ⓘ 2016-03 ⓘ 2017-05 ⓘ
matchLocation	London, England ⓘ surface form: London Seoul ⓘ Wuzhen ⓘ
notableAchievement	defeated European Go champion Fan Hui 5–0 in October 2015 ⓘ defeated Ke Jie 3–0 in May 2017 ⓘ defeated world champion Lee Sedol 4–1 in March 2016 ⓘ first computer program to defeat a professional Go player on a full-sized 19x19 board without handicaps ⓘ
notableImpact	demonstrated the power of deep reinforcement learning in complex board games ⓘ
notableWork	AlphaGo self-linksurface differs ⓘ surface form: AlphaGo Fan Lee Sedol ⓘ surface form: AlphaGo Lee AlphaGo self-linksurface differs ⓘ surface form: AlphaGo Master
operatingSystem	Linux ⓘ
opponent	Fan Hui ⓘ Ke Jie ⓘ Lee Sedol ⓘ
parentOrganizationOfDeveloper	Google ⓘ
programmingLanguage	C++ ⓘ Python ⓘ
sponsor	Google ⓘ
successor	AlphaZero ⓘ surface form: AlphaGo Zero AlphaZero ⓘ MuZero ⓘ
trainingMethod	reinforcement learning through self-play ⓘ supervised learning from human expert games ⓘ
uses	Monte Carlo tree search ⓘ deep neural networks ⓘ reinforcement learning ⓘ

Referenced by (26)

Full triples — surface form annotated when it differs from this entity's canonical label.

DeepMind → knownFor → AlphaGo ⓘ

DeepMind → developed → AlphaGo ⓘ

DeepMind → notableProject → AlphaGo ⓘ

this entity surface form: AlphaGo match against Lee Sedol

Demis Hassabis → knownFor → AlphaGo ⓘ

AlphaGo → notableWork → AlphaGo self-linksurface differs ⓘ

this entity surface form: AlphaGo Fan

AlphaGo → notableWork → AlphaGo self-linksurface differs ⓘ

this entity surface form: AlphaGo Master

AlphaGo → alsoKnownAs → AlphaGo ⓘ

this entity surface form: AlphaGo Lee

AlphaGo → alsoKnownAs → AlphaGo ⓘ

this entity surface form: AlphaGo Master

David Silver → notableWork → AlphaGo ⓘ

David Silver → notablePaper → AlphaGo ⓘ

this entity surface form: Mastering the game of Go with deep neural networks and tree search

AlphaStar → relatedTo → AlphaGo ⓘ

AlphaZero → parentProject → AlphaGo ⓘ

this entity surface form: AlphaGo project

MuZero → inspiredBy → AlphaGo ⓘ

Demis → knownFor → AlphaGo ⓘ

subject surface form: Demis Hassabis

Fan Hui → defeatedBy → AlphaGo ⓘ

Fan Hui → participantIn → AlphaGo ⓘ

this entity surface form: AlphaGo vs Fan Hui match

Fan Hui → participantIn → AlphaGo ⓘ

this entity surface form: AlphaGo–Fan Hui five-game match in 2015

Fan Hui → collaboratedWith → AlphaGo ⓘ

this entity surface form: AlphaGo development team

Fan Hui → hasNotableOpponent → AlphaGo ⓘ

Lee Sedol → opponent → AlphaGo ⓘ

Ke Jie → playedAgainst → AlphaGo ⓘ

Ke Jie → opponentInNotableMatch → AlphaGo ⓘ

Ioannis Antonoglou → knownFor → AlphaGo ⓘ

AlphaGo Zero → differsFrom → AlphaGo ⓘ

this entity surface form: AlphaGo Master

AlphaGo Zero → differsFrom → AlphaGo ⓘ

this entity surface form: AlphaGo Lee