I'm reading the book "Reinforcement Learning: An Introduction" (by Andrew Barto and Richard S. Sutton). 

The authors provide the pseudocode of the _prioritized sweeping_ algorithm, but I do not know what is the meaning of `Model(s, a)`. Does it mean that `Model(s, a)` is the history of rewards gained when we are in state `s` and the action `a` is taken? 

Does `R, S_new = Model(s,a)` mean that we should take a random sample from rewards gained in state `s` and action `a` is taken?