Supervised learning for a turn-based game?

So I have 4GB of turn-by-turn data for many games of a particular strategy game. It appears that most people interested in using ML to build an AI for turn-based games use reinforcement learning to build a model on the fly.

Since I already have really good data, can I use supervised learning to solve this task?

EDIT: I was considering using regression to assign a score to a given action based on its likelihood of eventually resulting in a win; is this the right way to think about it?

Topic game supervised-learning

Category Data Science

1
answered at

Maybe the correct way of addressing this is by making sub optimizations of every step, even though it could be done by regression, I would suggest decision trees.

You have and advantage: A game is made of discrete steps, so in every moment you can "stop" and decide the best move based on your (possibly comprehensive) history of moves.

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