Continuous vs. Batch learning

[Bill Skaggs]

>It is pretty clear to me that biological neural networks have all adapted
>to prefer the continuous learning technique, as we can verify for humans
>by remembering something that we only saw (or heard, etc.) once.  One-trial
>learning paradigms abound in the behavioral literature.  I cant think of 
>any biological examples of batch learning, in which sensory data are
>saved until a certain number of them can be somehow averaged together
>and conclusions made and remembered. Any ideas?  

  David Marr's theory of the hippocampus proposed that it (the 
hippocampus) is an intermediate-term memory storage device,
performing one-shot learning of experiences and then holding
them for a period of days or weeks until they can be evaluated
for significance and then gradually moved into the neocortex for
permanent storage.

  In my humble opinion this is still the best available
theory of what the hippocampus does.  Some of the details have
changed, but the basic idea still makes sense.

  Patrick Lynn has recently been exploring a more abstract version
of Marr's idea, using a "buffer" of example patterns to train a
recurrent back-prop net, with new patterns going into the
buffer, hanging around for a while, then dropping out.  He
has found that under certain conditions buffering gives
better performance than learning each pattern only when it
is presented.

(Reference:  "Simple memory: a theory for archicortex." D. Marr, 1971,
Phil Trans Roy Soc B 262: 23-81.)

	-- Bill Skaggs