So, I've decided that I can't possibly write a good algorithm for this until I've become at least 初段 (shodan), because a lot of complex concepts would help in drastically reducing the size of the decision tree just by the shape of the game. By generating and separating territory sizes and determining which ones are in danger, the computer can react a lot faster, doing a short search and singling out a few moves. I've risen from 30級 to about 24級 now, so I've still got a long way to go. In the meantime, it's time to start writing the paper... =(
Well, finally got around to doing *something*. Going to head up to Columbia in a week or two to oil up my rusty Japanese, and, of course, learn the game of Go, with the guys and gals of nyamigo. It sure doesn't help when developing something to not understand the requirements :)
I'll report back in 2 weeks how everything goes. (No committments, though...)
I'll report back in 2 weeks how everything goes. (No committments, though...)
The purpose of this site is to track the [super slow] progress of my development projects. I'm researching on my spare time the effectiveness of "lossy pruning" in Artificial Intelligence, because let's face it, when you sit down to play a game, you rule out many moves right off the bat if you're a skilled player. Why shouldn't the computer do the same? This may have many applications in high branching games, specifically computer go, where the number of possible moves is so high. Stay tuned! (Although don't keep your hopes up...)
