Path: utzoo!attcan!uunet!lll-winken!xanth!ames!mailrus!cornell!batcomputer!rpi!sun.soe.clarkson.edu!spam
From: spam@sun.soe!clutx.clarkson.edu (Roger Gonzalez,,,)
Newsgroups: comp.ai.neural-nets
Subject: Training
Message-ID: <2698@sun.soe.clarkson.edu>
Date: 19 Mar 89 20:28:03 GMT
Sender: news@sun.soe.clarkson.edu
Reply-To: spam@clutx.clarkson.edu
Lines: 20

Has anyone come up with a good way to train a net
without knowing a "target" in advance?  For example,
if my net is in an undesireable state S1, and it is
totally clueless about how to get to state S2, I would
like it to improve the connections that do get it to
state S2, and impede any others.  Now, since it has
no data at all to go on, and the only info it gets after
1 pass is "nope, not in state 2 yet", what can I use as
a target?  All the learning methods I've studied so far
are inadequate for this.

Thanks in advance,
-Roger



++ Roger Gonzalez ++ spam@clutx.clarkson.edu ++ Clarkson University ++

   "Just like I've always said; there's nothing an agnostic can't do
    if he's not sure he believes in anything or not!" - Monty Python