From: ken@iat.holonet.net (Ken Easlon)
Newsgroups: comp.ai.philosophy
Subject: Re: The Complexity Required for intelligence
Date: 15 Dec 92 21:07:31 GMT
Organization: HoloNet National Internet Access BBS: 510-704-1058/modem



In article <101972@netnews.upenn.edu> ,
wagner@hp800.lasalle.edu (Jon Wagner) writes:

>...thoughts about the complexity of systems and AI...

Being uneducated to the extreme, I can't talk about Turing machines and
abstract notations for complex concepts.  However, I am concerned about how
much computer power it would take to emulate human consciousness.  I think
we can take a step toward an answer by understanding how many bits it would
take to model some of these concepts.

Consider an entity in it's environment.  Absolute minimum, 2 bits, one for
the entity, one for the environment.  Say we're talking about the concept
of existence.   In this model we have two degrees of existence, 0 and 1. 
We could define these degrees in absolute terms, 0 = no existence, 1 =
complete existence.

Or we could use a more practical scale, 0 = not enough existence (or
probability of existence) to worry about, 1 = enough to consider.  This
particular definition is tilted toward the concept of non-existence.  

If we say 1 means enough existence (or probability) to REQUIRE our
attention, then 0 would mean no existence or enough existence to consider,
but not enough to require our attention.

We can get around this complexity by allowing as many bits as it takes to
define the scale with sufficient resolution to meet our practical needs.

At this elemental level, let's just use a one bit scale for degrees of
existence, and put the threshold at the point where we can assume existence
beyond a reasonable doubt.

Say the right bit is the entity, and the left bit is the environment.

00 maybe they exist, maybe they don't, who cares.
01 the entity exists, can't be sure about the environment.
10 the world goes on, but the entity is dead.
11 agreement, there is an entity in its environment.

Now to flesh out the concept.  How do we imagine this concept of an entity
in it's environment.


             1                1 1               1 1 1
           1 1 1             1 1 1              1 1 1
             1                1 1               1 1 1

          ORTHOGONAL       HONEYCOMB      ORTHOGONAL & DIAGONAL

The entity is the one in the middle.  The ones on the fringe are sectors of
the environment.  Eventually I'm going to be working my way up to
multidimensional arrays of bits, and I find them easy to imagine as
assemblages of cubes, so I'm going to use the rectangular model and
consider the environment as being neighboring points in all 8 directions.

Now we're up to 9 bits, the entity and its environment in two dimensions.
In three dimensions we're talking 27 bits, a cube 3x3x3 with the entity in
the middle.  Let's add in the time dimension, 3 cubes, past present and
future, 81 bits.

Since we're talking about intelligent systems, the entity needs a model of
itself in it's environment.  Break down the center cube into 27 pieces,
with the outer pieces (of the central cube) representing the model of the
environment, and the center most bit the model of the entity.  Now we're up
to 53 bits per cube, 156 for three time samples.

The entity consists of more than just a model of self in environment, there
must be a body.  Ok, the central 27 bits, minus the extreme central bit,
now represent the body, and the extreme central bit is is now broken down
into 27 pieces to represent the environmental model with the entity in the
middle.  Another 26 bits per cube, total 79 per cube, 237 for 3 time
samples.

Of course the entity needs some self awareness, so inside the model of the
environment, a model of the body, another 26 bits per cube, 3 time slices,
total 315 bits.

Let's recap here.  We have a cubed onion, each layer has 26 bits.  If we
keep everything cubic, each layer is 3 times as thick as its neighboring
layer toward the core, and 1/3 as think as its neighboring layer toward the
surface.  These ratios are only important when it comes to imagining all
these bits as cubes within cubes.  At some point we're going to have to go
abstract and think with symbols.

But, at this point, let's stick with the cubed onion.  The outer layer is
the environment, the next layer in is the body, the next layer in is the
model of the environment, and the next layer in is the model of the body.

The little cube in the very center hasn't been broken down yet, but it
interfaces with the model of the body.  Let's call it the body model
operator BMO.

For the entity to act intelligently, it must be able to sense changes in
the environment, via the environmental model, and consider a number of
possible reactions by using the BMO to guide the model body through a
sequence of modeled moves in the environmental model, and to calculate what
effect these moves would have on the environmental model, and thus to
anticipate future sensations from the environment via the model.

The centermost of the three time sample cubes is the present moment.  This
is where the BMO senses environmental changes and makes instinctive-reflex-
intuitive moves.  If the move requires thought, the BMO models the move in
the future cube.  If it needs stored information it gets it from the cube
representing the past.

Of course with a complex past, and a complex itinerary for the future,
we're going to need more than three time slices.  

And then there's the problem of the BMO itself.  How much complexity is
required to form our concept of body operation.

Obviously there's a lot more work to be done, but with just 315 bits, we
can set up a model that addresses many of the problems associated with AI.

I think if we extend this line of thinking, by the time our model has
reached the complexity of a few kilobytes, we could be talking some serious
shit.  

--
Ken Easlon
ken@holonet.net
Newsgroups: comp.ai.philosophy