You've been logged out of GDC Vault since the maximum users allowed for this account has been reached. To access Members Only content on GDC Vault, please log out of GDC Vault from the computer which last accessed this account.

Click here to find out about GDC Vault Membership options for more users.


Session Name:

Rolling the Dice: Leveraging Monte-Carlo Tree Search in Game AI


As the complexity of potential state spaces that AI agents have to explore moves beyond more traditional games like chess, search-based approaches like minimax are no longer feasible to employ. Worse, when imperfect information is involved, the problem becomes largely intractable. What is needed is a way of exploring that multi-layered possibility space and coming up with a "good enough" answer, even if it isn't the "mathematically perfect" one, and still do it in a reasonable amount of time. Using examples from a suite of successful commercial mobile games, as well as the winner of the annual StarCraft AI Competition, this session explains how Monte-Carlo Tree Search (MCTS) works and how it has become a viable tool for AI agents in a wide variety of games.

Did you know free users get access to 30% of content from the last 2 years?

Get your team full access to the most up to date GDC content

  • GDC 2014
  • Nathan Sturtevant
  • University of Denver
  • Jeff Rollason
  • AI Factory, Ltd.
  • Peter Cowling
  • University of York, UK
  • David Churchill
  • University of Alberta, Canada
  • free content
  • AI Summit
  • AI