6883e621_ws___Machine_Learning__Theory___3
[0] RL, POMDP learning [1] Learning is about finding and acting according to a near optimaly policy in a Partially Observed Markov Decision Process [2] In a sense, we’ve made no assumptions, so algorithms have wide applicability. [3] 
All known algorithms scale badly with the number of hidden states.
All Models of Learning have Flaws « Machine Learning (Theory)
3