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I think you raise a good question, especially WRT to how the NNs inputs & outputs are mapped onto the mechanics of a card game like MtG where the available actions vary greatly with context. I don't have a really satisfying answer to offer, but I have played Keldon's Race for the Galaxy NN-based AI - agree that it's excellent- and have looked into how ...

You would definitely want your network to know crucial information about the game, like what cards AI agent has(their values and types), mana pool, how many cards on the table and their values, number of the turn and so on. These things you must figure on your own, the question you should ask yourself is "If I add this value to input how and why it will ...

This is completely feasible, but the way the inputs are mapped would greatly depend on the type of card game, and how it's played. I'll take into account a few possibilities: Does time matter in this game? Would a past move influence a future one? In this case, you'd be better off using Recurrent Neural Networks (LSTMs, GRUs, etc.). Would you like the ...