Hi, so I have trouble where to start with this one.
Like, given how the AI works, I can rather easily write a function that counters all 4 of them for 100% - but only if they are in a specific order playing 1000 turns each (well technically I could even use the code to just hardcode the 4000 responses) - but that’s obviously not the goal.
So my issue comes down to what my goal is and what kind of model would be appropriate, because I am not dealing with static data and predictions, but 4 different functions that change their output based on my input.
What bothers me is, what constrictions I should look at for ML.
Should I consider both the order and turn-number of the bots as random? Then maybe LSTM seems likely, though could that even handle the change in strategy?
Or are they fixed? Then I could go with Reinforcement Learning and just let it basically create the 4000 ideal responses mentioned before.
In theory I could also go with a basic ML-model, give it 4k inputs with no hidden layers (or a non-dense 4-node hidden layer for each bot) and let it optimize that.
Though none of these options feel really good.
Would be happy for any kind of advice on how to approach that challenge with ML rather than just coding the counter myself.