University of Hertfordshire

By the same authors


  • Jialin Liu (Editor)
  • Tom Schaul (Editor)
  • Pieter Spronck (Editor)
  • Julian Togelius (Editor)
  • Christoph Salge
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Original languageEnglish
Pages (from-to)67-114
Number of pages48
JournalDagstuhl Reports
Publication statusPublished - 14 Apr 2020


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.


© 2020 Pieter Spronck, Jialin Liu, Tom Schaul, and Julian Togelius. Except where otherwise noted, content of this report is licensed under a Creative Commons BY 3.0 Unported license:

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