Here's a fun, frivolous, and simple little program I wrote recently 
which seemed just interesting enough to share.  The idea is to write an 
AI assistant for the game of minesweeper.  The trickiness is that 
sometimes every available square has a chance of having a mine on it, so 
running a basic constraint satisfaction algorithm on it won't give you 
any useful information.

Instead, you can generate a sequence of random mine assignments which 
are each consistent with the numbers on the currently visible squares 
and then calculate a running average of the probability that each square 
has a mine.  In some cases this probability is 100% or 0%, in which case 
it (with high likelihood) gives you the same result as a standard 
logical deduction would, but in other cases the probabilities are very 
useful for making a move.

It's fun to watch the colors flicker around and then quickly converge to 
an answer, and to see the ways in which different patterns interact with 
each other.  Attached are a couple of screenshots.  Blue is low 
probability and red is high probability.  Squares with 100% or 0% 
probability are highlighted with a white border.

Post a reply to this message

Attachments:
Download 'monte_carlo_minesweeper1.png' (10 KB) Download 'monte_carlo_minesweeper2.png' (12 KB)

Preview of image 'monte_carlo_minesweeper1.png'

Preview of image 'monte_carlo_minesweeper2.png'