From: ericjohn@sal-sun53.usc.edu (Eric Johnson)
Newsgroups: rec.org.mensa
Subject: Re: Atheism and Intelligence
Date: 21 Dec 1992 15:50:17 -0800
Organization: University of Southern California, Los Angeles, CA
Distribution: world
NNTP-Posting-Host: sal-sun53.usc.edu


+  8787	Re: Atheism and Intelligence                  [66] Lotus               In article <1992Dec18.062438.6456@linus.mitre.org>, crawford@boole.mitre.org (Randy Crawford) writes:
|> In article <1992Dec16.231131.1173@umr.edu> S106495@UMRVMA.umr.edu writes:
|> >Another alternate logic I am
|> >speaking of is neural networks.  These are        computer algortithms
|> >where the machine takes the factors toward a given         conclusion,
|> >and thru trial and error perfects an algorithm to give a conclusion.

NNs aren't 'alternate' logics, but (as you said) algorithms. Everything
that they do can be expressed in terms of starndard logics.

|> Not `a' conclusion.  NNs can only lead you to `the' predetermined conclusion.
|> NNs are useful only when you know the goal state, but don't know how to
|> get there.

You are confusing the training of a neural net with it's operation. Yes, 
to train a NN, you must have a known goal state(s) handy, much as you 
would need a training example to teach a human to do something. The 
operation of a neural net isn't 'trial and error' at all; it uses 
the relations it learns in the training phase to come to a conclusion.
Unfortunately, these relations are expressed in a way that is not 
directly understandable to humans - using a NN, we *still* don't know
how to get there... Neural nets can be trained to perform logical
inferences and deductions... the one in my head is!

|> In no way do NNs resemble _any_ form of logic equivalent.  Trial and error is 
|> not a form of reasoning -- it couldn't be.  In logic, you don't yet know the 
|> conclusion you need to reach.  You have confidence that in the use of the 
|> method (which you understand and can verify) and that you will reach a 
|> reproducible and valid conclusion.  In trial and error, you know the conclusion
|> but not how to get there.  How then could you use trial and error to reach a 
|> logic-like conclusion when you can't tell at each step whether you have made 
|> any forward progress since you don't know what the conclusion is nor if you're
|> approaching it?

Even discounting the fact that neural nets don't use trial and error to 
solve problems, you are still wrong. Reasoning doesn't operate in a
vacuum - you attempt to prove or disprove conclusions, or at least to
derive conclusions which have certain desirable properties. Otherwise,
your reasoning process would never produce a result. Reasoning can be
viewed as a search problem through the space of possible conclusions, 
and generate-and-test is one possible search strategy. You could use
trial and error both to select likely conclusions to attempt to prove
or disprove, and also to guide your reasoning process each step of the
way to the solution. 

|> >Some balance must be struck
|> >between the two for many tasks, especially   creativity and problem
|> >solving.  There is no algorithm to come up with new ideas, but you can't
|> >just "use the force" to get them either.  Neural networks will probably
|> >be able to solve some problems using neither gut instinct nor syllogisms.  
|> 
|> I don't think NNs have ever solved _any_ problems.  Nor will they ever.  Like
|> genetic algorithms, they are simply a tool for finding your way blindly from 
|> a place you know to another place you know, via a path you don't know, and 
|> only when you can determine whether each step takes you nearer or farther 
|> from your destination.  You use them to search for something, not tell you 
|> what you are searching for.
|> 
|> This is not to condemn neural nets or genetic algorithms in any way.  However
|> they can never take the place of logic nor even supplement it.  They are not
|> reasoning methods; they are search methods.  Logic is a reasoning method -- 
|> the only one in which I have any experience or confidence.

Again, reasoning is a search method! NN and GA wouldn't replace or 
supplement logic, but implement it.

I think the larger issue is partially a matter of perspective. Love is 
ultimately the result of an extremely complex physical process, which 
certainly follows logic. The fact that love can be reasoned about, however,
does not mean that it is itself the result of a reasoning process. 
Some of the factors influencing it are purely physical (perhaps the smell
of the loved one is physically pleasurable), some are the result of 
cognitive processes which are not reasoned (the smell triggers an 
association with some pleasurable past memory), some are the result of 
reasoning processes which occur below the conscious level (the loved one
thinks highly of you, which increases you self-esteem; thus s/he helps
to satisfy another high level 'drive'), and some are on the conscious level
("I respect his/her integrity"). There's plenty of interplay between 
levels, and since most of what's going on is not directly accessable to 
the conscious mind, it's easy to believe that there's no reason for it.

If we try to introspectively analyze the workings of some of our 
subconscious processes, we run up against a wall. It's easy to say 
that since these things just seem to appear in our minds, there's no
reason for them, they just are. This is like primitive men saying that
rain falls because it falls - there's no reason for it (until they 
invent a god to explain it). If there truly were no reason for love 
other than just because, why is it a persistant phenomenon? We don't
randomly fall in love and out of love with toasters and farm animals
every two minutes (well, most of at least :-)). 
-- 
Eric Johnson		Remember, It's good to keep an open mind, 
ISX Corp.		but not so open that your brains fall out...
(818)706-2020
ericjohn@usc.edu