Path: utzoo!utgpu!news-server.csri.toronto.edu!cs.utexas.edu!sun-barr!rutgers!att!cbnewsl!apr
From: apr@cbnewsl.ATT.COM (anthony.p.russo)
Newsgroups: comp.ai.neural-nets
Subject: Meta-Nets
Keywords: discussion, debate sparker
Message-ID: <4670@cbnewsl.ATT.COM>
Date: 20 Mar 90 13:13:18 GMT
Organization: AT&T Bell Laboratories
Lines: 29

I don't want to put a damper on the idea on Meta-nets, but
I would like to spark some debate on their use. Clearly,
the idea of using one network to teach another is an important
step toward emulating the human thought process.

However, from the discussions I've read lately, I have doubts as to
whether such efforts will prove fruitful. Here's why.

We could, in principle and probably in actuality, train a net to
teach other nets. I don't argue with that. However, the meta-net
has been trained by some standard algorithm. What we have then,
is a standard algorithm (say backprop) that is a teacher 
of a teacher (the meta net) of a learner (other networks).

I tend to think that the meta net, at best, would learn to
implement the standard algorithm. That is, we are training it to
learn some known algoithm. If this is the case, why not just use 
the standard alg and skip the meta net?

If this is NOT the case, then how do you propose to train the meta net?
I'm interested in any ideas addressing this.

 ~ tony ~

	~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
	~  	 Tony Russo		" Surrender to the void."	~
	~  AT&T Bell Laboratories					~
	~   apr@cbnewsl.ATT.COM						~
	~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~