Over the last week we have been having fun creating a mini-sample submission based on the board game Go demonstrating:
The mini-game sample itself actually uses a rule based AI and should not be seen as an example of AI or game quality - more a sample of documentation quality and the submission files required. What we do hope is that you will find the sample a useful reference on how to document your code (specifically the XGoLibrary project), how to comment code you have taken from other sources and how to write the design summary.
If you have any questions on the code, documentation or design summary, please post in this thread.
Update 1: We have fixed a couple of small issues and updated the submission found at the link:
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We have noticed that the PDF still had some review comments; they are removed now.
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Rendering during the scoring was accidently reset to constant black rather than an alpha value proportional to the expected propability of the territory outcome. This is fixed now (it was actually commented out before).
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We slightly refined the passing algorithm of the AI: If the human player passes then the AI uses the Monte Carlo scorer to estimate whether or not each piece is already determined in colour up to a probability of at least 80%. If so, the AI passes already.
Update 2: We have fixed one further bug and improved the Monte Carlo scorer significantly. For more information, have a look at the sample download.
Please let us know if you have any further questions.
Best of luck to everyone, Merry Christmas and a happy New Year 2008,
Ralf Herbrich, Thore Graepel, Phillip Trelford & Joaquin Quiñonero Candela, Microsoft Research Cambridge
