Model Design Theory Tips/Tricks/Docs (for a card game agent)

I am currently trying to get a bit more into ML, for me that means playing with it in some context I know already or applying it to something interesting - either way I am aware this whole endeavor is a bit of stretch and having a good grasp on machine learning requires a good mathematical knowledge.

In my off time I have been recreating a digital copy of a table card game called Scout: For The Show and I had the great idea to try and make an autonomous agent based on Machine Learning for it (definitely the best starting idea /s but there is still a lot to learn in failures).

First, I did the naive thing, imagined the inputs and outputs from a players perspective - current hand, amount of turns taken, count of cards in other player hands, … but my intuition tells me this is in some way very wrong (?), the “shapes” of these inputs/outputs are weird - I don’t think the model would respond with a valid move anytime soon during training like this, if ever.

Second, I’ve then searched far and wide for card games and machine learning and found some resources where they usually reduce the problem space as much as possible and apply the model only on a subset of the information (often represented in completely different formats/dimensions - Markov Decision Process).

Obviously I am not asking for the mathematical analysis of the game in question, in broad sense I am looking for any kind of pointers that might apply here, I am aware this is a very brute-force approach for something that should be carefully mathematically analyzed and from that a model could be derived.

Thanks for any pointers, wisdoms or ideas!


Notes:
I am coming from a software development background - Python mainly, so it’s not that far for me programming wise, and I have already played with YOLO models though only as user.

The Scout card game has 45 cards with a number (1-10) on the top and bottom, the main objective is to capture points by playing stronger card combinations, either pairs/triples/x of a single number (1-1-1, 9-9, …) or sequences/straights (2-3, 5-6-7-8, …).
The twist is that cards in hand can’t be moved or flipped around, only the top side number is important for most of the game (and each variation of the top/bottom numbers is contained only once, 1/10 and 10/1 is the same card, only flipped).
Players take turns in either playing a new hand on the table (Show - capturing the remaining hand, scoring) or taking a one card from the table (Scout) and putting it anywhere in their hand, even flipping top/bottom)

Resources I have found:
www.youtube.com/watch?v=IQLkPgkLMNg (Great explanation of the problems with solved/unsolved games, minimax, MCTS etc)
www.youtube.com/watch?v=vXtfdGphr3c (Reinforced Learning)

howrar,

You’ve read a bit on MDPs, which is a good start. You may also want to look into reinforcement learning for how to optimize said MDP.

taaz,

Thank you very much, I was not sure if it’s the right direction.

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