Game-AI Forum

I've completed a fairly successful computer player, and will sketch the algorithm here. The overall algorithm is a simple static evaluation maximizer, without search. The evaluation has only a few components: the number of edges currently contacted (0-3) and the number of own-color tiles currently o...

refer to https://boardgamegeek.com/boardgame/43096/wyps Its a word game, whose winning conditions are like the Game of Y - that is, connecting three sides of a triangular board. The interesting thing about this is that the winning condition has basically no relationship to the tactical game play, wh...

Regarding using neural nets for games. Doesn't it seem odd that we take a domain of perfectly discreet objects - black stones, white stones, squares on the board, and re-represent it as floating point numbers with thousands of parameters? It seems like there ought to be an approach that uses similar...

I've been using Hex on a 7x7 board as a test bed. My basic approach is to use the visit counts at top level of a MCTS search as the target; make the network learn what the visit count should be, and use that prediction to weight the random playout phase of new searches. I understand this is the basi...

Here's a visualization of how a MCTS search evolves.
https://www.youtube.com/watch?v=FvRSxNLTg7U

Leela Zero is a green-field effort to reproduce and explore the methods used by Alphago zero which I've been following. http://zero.sjeng.org/ It seems to be having some success, and it's open source. The general archecture it uses is a NN similar to the one described for Alphago zero, which guides ...

Inspired by Alphago and Alphazero, I've started exploring NN methods for game AIs, and neural nets in general. For starters, I found that there are no good forums for general discussion, hence this Machine Learning section, and this post. I'm kind of a bottom-up guy, I like to understand the stuff I...

Tintas is an abstract strategy game involving collecting colored tokens. https://boardspace.net/tintas/english/tintas-rules.html If you were trying to design a game to be a perfect vehicle for MCTS, this would be it. There are a maximum of 49 moves in the game, and usually the branching factor is 6 ...

Thanks! FWIW, back in the stone age of computing I struggled to collect about 5K professional games.

One caveat about this data set; a lot of the file names include unicode characters, and a lot of the files contain UTF-8 text.
A lot of tools will behave badly because of this.

The depth is fixed, but maybe you missed the point. For the same pair of evaluators, the one tuned to win at 1-ply does much worse if the search is deeper. For the actual evaluators I was testing, the actual playing depth is 5 or 6 ply, and it just didn't work to use a 1-ply search as a proxy to sel...