I have a set of 15 unique playing cards from a deck of 52 playing cards. A given state is represented by the respective card values in the set of 15 cards, where the card value is a prime number associated with that card. For example,
AH is represented by
How should I represent a single state for the NN? Should it be a list of the 15 prime numbers representing the list of cards? I was hoping that I could represent a single state as the sum of each of all 15 prime numbers and then throw that sum through a sigmoid function. My concern, however, is that the NN will lose information if I reduce the dimension of the state to a single attribute (even if that attribute is unique to that state - the sum of
n prime numbers is unique compared to the sum of any other
n prime numbers).
How important is the dimensionality of each state for Deep Q Learning? I'd really appreciate even some general direction.