Building a state of the art AI to play Magic: The Gathering, Melvin Zhang compares different algorithms and iterates on implementations. Initial experiments show Monte Carlo tree search (MCTS) outperforms minimax when given more thinking time. Later work focuses on developing an honest, non-cheating MCTS for Magarena that does not require all cores for parallelization. Open problems remain in improving play when losing and reducing unfun games.

1. Building a state of the art AI to play
Melvin Zhang

2. http://meowthegathering.tumblr.com/post/96620097852/mirri-debuted-in-exodus-but-still-looks-like-a

3. https://code.google.com/p/magarena/

4. http://afflictor.com/2012/09/11/chess-programs-regularly-play-at-good-amateur-level/

5. http://jonathanschaeffer.blogspot.sg/2012/08/chinook-twenty-years-later.html

6. http://games.cs.ualberta.ca/project/

7. http://news.discovery.com/tech/i-for-one-welcome-our-new-computer-overlords.htm

8. http://mathworld.wolfram.com/Go.html

9. http://madamepickwickartblog.com/2010/06/bite-the-hand-that-feeds-you/

10. https://www.wizards.com/sideboard/images/ptbos02/759.jpg

11. 1. Solve a simpler problem

12. http://www.gatheringmagic.com/nickvigabool-design-analysis-05202013-value-of-vanilla-creatures/

13. http://www.gatheringmagic.com/nickvigabool-design-analysis-05202013-value-of-vanilla-creatures/

14. 2. Choose the right algorithm

15. http://cardforge.org/

16. http://archive.wizards.com/Magic/Magazine/Article.aspx?x=mtg/daily/feature/44

22. Comparison of cheating AIs
At 1s thinking time:
Minimax MCTS
1 0.84

23. Comparison of cheating AIs
At 1s thinking time:
Minimax MCTS
1 0.84
At 4s thinking time:
Minimax MCTS
1 1.53

24. Date: Sun, 4 Mar 2012 21:04:39 +0800
From: Melvin Zhang
To: P. I. Cowling
Subject: Applying MCTS to make all AI decisions
...
Our own internal comparison with the original minimax AI confirms
that MCTS has better performance than minimax.
I hope that our preliminary findings and implementation would be
helpful to you and your team in further research in this area.
Regards,
Melvin

25. 3. Iterate, iterate, iterate

26. Monte-Carlo Tree Search without cheating
Issue 92: Reported by eolebigot, Nov 12, 2011
Would it be possible for Magarena to have a *non-cheating*
Monte-Carlo Tree Search? I tend to avoid the cheating AI,
because I prefer fair games, so an MCTS that does not cheat
would be great!
https://code.google.com/p/magarena/issues/detail?id=92

27. Date: Thu, 30 Aug 2012 12:33:13 +0100
From: P. I. Cowling
To: Melvin Zhang
Subject: Re: Applying MCTS to make all AI decisions
...
We remain interested in MCTS for Magic:The Gathering...
see our new paper at
http://scim.brad.ac.uk/staff/pdf/picowlin/CowlingWardPowley2012.pdf
Cheers,
Peter

30. Monte-Carlo AI not fully parallel
Issue 344: Reported by eolebigot, Apr 28, 2013
For the cheating Monte-Carlo AI, 2 cores are used
(instead of 4 thanks to hyperthreading). While this
may be normal, this is quite unusual.
For the non-cheating Monte-Carlo AI, only 1 core is used.
https://code.google.com/p/magarena/issues/detail?id=344

32. Comparison of honest AIs
At 1s thinking time:
Minimax MCTS
1 0.88 (0.84)

33. Comparison of honest AIs
At 1s thinking time:
Minimax MCTS
1 0.88 (0.84)
At 4s thinking time:
Minimax MCTS
1 1.71 (1.53)

34. Open problems

35. Open problems
MCTS makes bad plays when it is losing.

36. Open problems
MCTS makes bad plays when it is losing.
Reduce occurrence of games which are not fun.

37. www.firemind.ch

38. www.untap.in

39. magarena.googlecode.com