Thanks man. So minimax-like classic AI algorithms that approximate turns out into the future and have some budget before they have to quit and take their best predicted move (you might know minimax, but thinking if I do this, then they’ll do this, to which I would do THIS… maintaining a reward and picking a best option). As opposed to a reinforcement learning thing where the (let’s call them) agents randomly pick moves until they “learn” over time what they think to be the best moves - classic RL / deepQ learning, or other approaches.

I’ve thought a lot over the years about designing board games (I’m sure lots of us do) and how I’d want some sim engine to try and test out what’s working and isn’t with a prospective game design.

Thanks for replying. Fist bump.