License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagRep.9.12.67
URN: urn:nbn:de:0030-drops-120113
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2020/12011/
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Liu, Jialin ; Schaul, Tom ; Spronck, Pieter ; Togelius, Julian
Weitere Beteiligte (Hrsg. etc.): Jialin Liu and Tom Schaul and Pieter Spronck and Julian Togelius

Artificial and Computational Intelligence in Games: Revolutions in Computational Game AI (Dagstuhl Seminar 19511)

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dagrep_v009_i012_p067_19511.pdf (11 MB)

Abstract

The 2016 success of Google DeepMind’s AlphaGo, which defeated the Go world champion, and its follow-up program AlphaZero, has sparked a renewed interest of the general public in computational game playing. Moreover, game AI researchers build upon these results to construct stronger game AI implementations. While there is high enthusiasm for the rapid advances to the state-of-the-art in game AI, most researchers realize that they do not suffice to solve many of the challenges in game AI which have been recognized for decades. The Dagstuhl Seminar 19511 "Artificial and Computational Intelligence in Games: Revolutions in Computational Game AI" seminar was aimed at getting a clear view on the unsolved problems in game AI, determining which problems remain outside the reach of the state-of-the-art, and coming up with novel approaches to game AI construction to deal with these unsolved problems. This report documents the program and its outcomes.

BibTeX - Entry

@Article{liu_et_al:DR:2020:12011,
  author =	{Jialin Liu and Tom Schaul and Pieter Spronck and Julian Togelius},
  title =	{{Artificial and Computational Intelligence in Games: Revolutions in Computational Game AI (Dagstuhl Seminar 19511)}},
  pages =	{67--114},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2020},
  volume =	{9},
  number =	{12},
  editor =	{Jialin Liu and Tom Schaul and Pieter Spronck and Julian Togelius},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2020/12011},
  URN =		{urn:nbn:de:0030-drops-120113},
  doi =		{10.4230/DagRep.9.12.67},
  annote =	{Keywords: artificial intelligence, computational intelligence, game theory, games, optimization}
}

Keywords: artificial intelligence, computational intelligence, game theory, games, optimization
Collection: Dagstuhl Reports, Volume 9, Issue 12
Issue Date: 2020
Date of publication: 14.04.2020

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