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Does anyone know the technical details of how to train and AI bot for a game like poker?

I imagine it's just reinforcement learning where the inputs are the actions of the individual players (hold/fold/raise, timing etc) and the statistical probabilities in terms of expected cards. Train a neural net to predict probability of the opponent's hands and act accordingly.

Is it just that the professionals all act similarly enough that the bot can learn based on other players?



I'm sure the actual process differs from research group to research group. Here's how one commercially available AI training system claims to work.

http://www.pokersnowie.com/about/technology-training.html

And they go into some of the problems that stem from how they've abstracted the game here:

http://www.pokersnowie.com/about/weaknesses.html




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