From what I've seen, neural networks take a set of atomic inputs.
I want an input to be a variable array, i.e. a group of people (with unique IDs).
If I didn't care about their ID, I could simply feed a count of people as an input - but I do.
My thought are to have some form of forward-feeding, and iterate through each person, using their ID as an input to a node representing "insert entered room"
Does this make sense?
The same ID would be used in different nodes at different points. I.e to a "user left room" or "user sat down"
Also, how would one model two users interacting, atomically for inputs? I'm guess use 2 inputs representing "interacter A" and "interacter B"