How does the Forgetting curve change after repeated exposure to the same item we would like to memorise?
Currently, I am working on various demonstration graphs of various spacing effect algorithms.  From the research it seems like two of the parameters exist to constrain the outputted values...


  The parameters a and b are also assumed bounded between zero and one,
  and hence R(t) is similarly bounded, which must necessarily be the
  case as R(t) is a probability. Enforcing this bound is important as
  otherwise data fits can be inflated (see Navarro, Pitt, &amp; Myung, 2004,
  for further discussion).


I think Ebbinghaus' original function R(t) = e ^ -(t/s) (see this thread) can more easily explain things.  t is time and s is the strength of the memory.  After every review, s increases.
If you plot this out, you see that if you increase s, the forgetting curve function flattens out.