Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12258/3066
Title: Lessons learned from AlphaGo
Authors: Holldobler, S.
Keywords: Board games;Human players;State of the art
Issue Date: 2017
Publisher: CEUR-WS
Citation: Hölldobler, S., Möhle, S., Tigunova, A. Lessons learned from AlphaGo // CEUR Workshop Proceedings. - 2017. - Volume 1837. - Pages 92-101
Series/Report no.: CEUR Workshop Proceedings
Abstract: The game of Go is known to be one of the most complicated board games. Competing in Go against a professional human player has been a long-standing challenge for AI. In this paper we shed light on the AlphaGo program that could beat a Go world champion, which was previously considered non-achievable for the state of the art AI
URI: https://www.scopus.com/record/display.uri?eid=2-s2.0-85019836754&origin=resultslist&sort=plf-f&src=s&nlo=&nlr=&nls=&sid=44d90154573ea1cc971b53e97e0ea554&sot=aff&sdt=sisr&sl=174&s=AF-ID%28%22North+Caucasus+Federal+University%22+60070541%29+OR+AF-ID%28%22Stavropol+State+University%22+60070961%29+OR+AF-ID%28%22stavropolskij+Gosudarstvennyj+Tehniceskij+Universitet%22+60026323%29&ref=%28Lessons+learned+from+AlphaGo%29&relpos=0&citeCnt=0&searchTerm=
http://hdl.handle.net/20.500.12258/3066
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