For context, I’ve coded an engine for the boardgame Stratego, which is an imperfect information game. I’ve currently got a random "player" setup, and I have a bunch of functions setup to provide information to a future AI player, buuuut no AI player.
I’m currently doing a literature review to decide firmly on what I want, but I have little experience in building a neural network or such for a game. I have a database of some 20,000 games that I could train my AI on if I decided to go that route, but I’m also considering something evolutionary. Of curious note is that the database is for the game version that’s got a bigger board. I don’t like that version so I built mine to play the smaller board <( ^ ^ )>
I’m not entirely sure how I would implement these things. Bear in mind I have training in various forms of neural nets (RNNs, GANs, LSTMs… etc you get the idea) and other sorts of evolutionary methods and such, but I’ve never applied them to something like a boardgame.
As far as literature on stratego goes, I’ve read a few papers on Invincible (very good AI) and a few other bots but they weren’t extremely useful for what I want to do; I’ve talked to the maker of Probe (current best AI) about some things and he had good advice, but his AI isn’t of the type I’m pursuing. I’ve read some things about applying them to boardgames, but none give practical examples of training data really.
The current (probably a few hours outdated but I doubt you’ll be running it anyways) code is at: https://github.com/YWaller/StrategoProject If it piques your interest. I promise it’s only vaguely shitty.
I suppose my purpose is to get some ideas, some sources, and general help from you all >_>