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Let me second that, Roberto. While I never played checkers past childhood, I found it an interesting and often frustrating game then. That checkers is so complex and took such time and effort to solve may well indicate more complex games may resist complete analysis for a while, even with better computers and algorithms. Thanks for the write-up [the article summary, I believe]. Joe
Thanks Roberto for the very interesting comment. I was fairly big into checkers about 10 years ago and had read several books on it. Did you know that there are actually checker openings?
Anyway seeing that computers have solved a game (essentially a problem with 500 billion billion possible positions (5 x 1020); then I cannot help but wonder how many possible positions our various CVs have. With some of the very large games it must truly be a phenomenal number. Also, having large numbers of piece types... well, take Chess with Different Armies for example, the computers can have fun there. And Chu Shogi... wow!
In closing, the number for checkers is much higher than I would have expected.
Originally published in Science Express on 19 July 2007 Science 14 September 2007: Vol. 317. no. 5844, pp. 1518 - 1522 DOI: 10.1126/science.1144079 Prev | Table of Contents | Next Research Articles Checkers Is Solved Jonathan Schaeffer,* Neil Burch, Yngvi Björnsson, Akihiro Kishimoto, Martin Müller, Robert Lake, Paul Lu, Steve Sutphen The game of checkers has roughly 500 billion billion possible positions (5 x 1020). The task of solving the game, determining the final result in a game with no mistakes made by either player, is daunting. Since 1989, almost continuously, dozens of computers have been working on solving checkers, applying state-of-the-art artificial intelligence techniques to the proving process. This paper announces that checkers is now solved: Perfect play by both sides leads to a draw. This is the most challenging popular game to be solved to date, roughly one million times as complex as Connect Four. Artificial intelligence technology has been used to generate strong heuristic-based game-playing programs, such as Deep Blue for chess. Solving a game takes this to the next level by replacing the heuristics with perfection. Department of Computing Science, University of Alberta, Edmonton, Alberta T6G 2E8, Canada. Present address: Department of Computer Science, Reykjavik University, Reykjavik, Kringlan 1, IS-103, Iceland. Present address: Department of Media Architecture, Future University, Hakodate, 116-2 Kamedanakano-cho Hakodate Hokkaido, 041-8655, Japan. * To whom correspondence should be addressed. E-mail: jonathan@cs.ualberta.ca
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