AI game design

So AI game design is a thing: given a set of possible games defined by the pieces available, board, etc., come up with a "good" set of rules. What a "good" game is seems ... really human, but some exploration of using AI programming techniques to augment human game design has been done.

Here's a neat article. It's about exploring a very small game set using "Shibumi" equipment (released in October of 2011), which consists of a 4x4 set of holes and three colors of marbles to be played on those holes and stacked on one another to make pyramids. That totals up to 30 possible positions, which can be empty, white, black, or red (two bits each), so the set of possible board positions is encoded in 60 bits.

Turns out evolution isn't so hot for game design - the universe is too uneven to allow much gradual improvement. They've been having success with "Monte Carlo tree search", building trees using a semi-random process. Kind of neat. They want to compare it with GA in finding new games in this universe.

Their fitness function has to be playability as judged by a human.

Here's a notion: judge playability by determining how challenging it is to evolve a good player. Or something. That is to say, automate both ends of the process.