[Paleopsych] exploration in genetics and other intelligence

[Werbos, Dr. Paul J.]

Hi, Howard!

I was a bit too brief on some important ideas you raised. Let me try to 
correct that.

You said:
>Paul's words suggest that restlessness and boredom have been a key part of 
>this learning system.  I've been calling this a restless cosmos, a driven 
>cosmos, an obsessive compulsive cosmos for a very long time.  But Paul is 
>suggesting that we make computer-based learning machines restless 
>too.  That we make them try out new possibilities just for the hell of it, 
>just to evade the pain of boredom, the pain of staying precisely the same, 
>the pain of ennui.  Paul is on the brink of suggesting that we make 
>computational programs hunger for pop culture, for music and games that 
>test and expand the silicon brain in new ways.
>
>Paul is suggesting that genes may be as restless and boredom-prone as 
>Baudelaire, who painted ennui as the ultimate pain.  He's suggesting that 
>on the sly, when they're not working, genes play around and dance in 
>leisure time.  Or at least that's what Paul's ideas inspire in me.
>
Basically right. Exploration is an unavoidable issue in designing true 
intelligent systems.

>I know that leisure, entertainment, pop culture, art, and play are not 
>useless.  I've known it since I began my 20 years of fieldwork in these 
>fields--poetry, art, magazine publishing, and finally popular music.  Paul 
>seems to be whispering to me that these cultural expressions may be a 
>stochastic search for new possibilities.  And his words suggest to me that 
>genes play games too.  They play the sort of musical games--establishment 
>of a theme, then variation on it--that Greg's mechanisms make possible.
>
>Paul, my apologies if I've bent your words, but they're extraordinarily 
>evocative.
======================================================

The word "intelligent" has many definitions -- especially in marketing by 
Beltway Bandits.
I have explained at length why I would say that TRUE intelligent systems 
all involve
some kind of optimization... some kind of learning to "best possible 
results" by some
kind of measure of success. Let me not revisit all that just now. (There is 
a book
edited by Dan Levine, Optimality?... and lots of stuff I cite in my papers 
at arXiv.org,
in the quantitative biology part.)

Now... in really complex environments, the optimization always comes down to
"nonconvex optimization" -- optimization in a situation where there are lots of
LOCAL optima, like deceptive foothills on the way to the highest mountain peak.

There are actually some very sophisticated and successful engineering 
systems, which are
worthy of being called "intelligent" (I feel, for complex reasons), which 
do not have a real
systematic exploration component. But to be truly brain-like, they need 
that, in order
to perform well in complex nonconvex environments. Conversely, there are 
some very simple
genetic algorithms, not at all brain-like, which do very good nonconvex 
optimization
AT A GIVEN TIME, SUBJECT TO USING NO PRIOR INFORMATION -- but have many 
limitations.
They are very useful in engineering today, in part because no one has 
implemented anything more
truly brain-like for these kinds of applications. (Though I know some 
people who would
say that is changing -- people like Thaler or Wunsch or Serpen.) They are 
the best
state of the art, on the whole, for problems like exploring the space of 
possible designs for
antennas to do specialized tasks as well as possible, and things like that.
They are used in the best real-world Optimal Power Flow packages used by
electric utility companies.

------------

OK, so exploration is necessary for the higher capabilities...

BUT

This does not mean that intelligent people have to try drugs or color their 
hair pink.
(Though I have known some who went through that, as most of you have.)

In fact -- in my own theory of how the brain works (the part summarized in 
just a few places, like
chapter 10 of my book Roots)..

I would say that the essential difference between the wiring of the original
basic mouse brain and the wiring of the human brain
is that humans don't have to learn form their own mistakes.
They have an inborn ability to learn from the mistakes of others
instead.

And that's where we started our discussions, Howard. I was really hoping 
that you
and David Smith and I could joint author a more popular (or humanistic paper)
on the fundamental revision of Freud's theory of dreams implied by this 
theory of how
the wiring works. The claim that our human brains are hard-wired to commonly
give us dreams presenting the viewpoints of OTHER humans. The implications
are extremely far-reaching in my view, not only for theory but for improving
our ability foster human growth, one of the very most fundamental issues
on the table in the world.

All for now.

Best,

    Paul 
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