Logan,

Yes, as I said, I could see  you have a loose sense of what is needed (any 
sense can only be “loose”).

However, your idea that your robot can do this by an algorithm is parallel with 
Jim’s that complexity is involved.

You can only have an algo for a journey if you have already made the journey, 
and can predict the territory, – and have a route[s]-map. (That incl. “ 
replotting alternative ways of getting there” after meeting unforeseen 
obstacles).  By extension, you can only have problems of complexity if you 
already have a known set of possible journeys/route-maps to consider (a la 
Travelling Salesman Problem)..

That’s why algos only work in artificial controlled environments like 
factories, labs and warehouses, which are fully known and have been 
artificially structured to be predictable..

To be able to travel in the real world, is to travel through *unpredictable* 
and *more or less unknown” territories. We want robots which like living 
creatures can “go through that field” or street or room *blind*  - just like 
you -  through an “unstructured field” with “unknown obstacles” -   i.e. 
without ever having seen it before, or encountered anything quite like it, or 
having any route-map. They will have a rough idea of what such travel may 
involve – know some of the steps that may be needed to go through a room – but 
have only partial knowledge of what is needed. The journey can’t be 
algorithmically plotted in advance – it can only be made up as you go along,  
and usually requires some innovation – experimenting with the body to take some 
new or different kinds of steps.

Narrow AI/algos are for rational problems, when you already know the way[s] to 
the solution and the goal – already have the route-map.  AGI is about creative 
problems when you don’t know the way[s], don’t have a route map  – and have to 
make it up as you go along. All creative problems whatsoever are like this.

If you think different, try it. What’s the algo for going through “that room”? 
Oh no, you don’t get to know what the room is in advance. You have to write 
your algo [sight of room unseen] in advance.Try it. And only then will I tell 
you what the room is and what’s in it. ... 

You can’t plan for the real world. You’ve got to “take it as it comes.”  

From: Logan Streondj 
Sent: Sunday, December 16, 2012 6:04 PM
To: AGI 
Subject: Re: [agi] Internal Representation

In terms of actual movement, that is done quite similarly,
to how we have an interpreter with input and output on a screen,
simply the outputs go to motors, and inputs are sensors.

For the actual "drivers" I was intending to have the AI algorithms available in 
HSPL by that point, so that the GI could evolve drivers to work with the 
hardware it has available, and potentially work around hardware failures. 

So crawling would be defined as a form of locomotion using arms and legs with 
torso parallel to the floor.  Based on a  similarly simple description, it 
could then evolve a process involving the sensors and actuators it has 
available.    Similar to snake robots it would be able to adapt to changes in 
it's configuration, and layout of objects. 

In terms of "fluidity" that is part of the process,  as the course itself is 
simply a rough outline of the journey,  the walking algorithm would evolve to 
take into account obstacles and such as part of the evolution of the walking 
driver. 

If for instance there is some unforseen obstacle, the plot could be replotted, 
for alternative potential ways of getting there.  This is exactly how humans, 
do it, likely most animals as well,   for instance they figure out where they 
are going to jump before jumping there. 
And if they are going to get water, they figure out a good path to take to get 
there, before actually setting out. 






On Sun, Dec 16, 2012 at 12:43 PM, Mike Tintner <[email protected]> wrote:

  PM: You must say why it cannot be done to be helpful, which you haven't. 

  I would have thought a man with your imagination wouldn’t need to be told – 
the principal reason you cannot have a complex set here,  is that you cannot 
define or calculate a) the trajectories or lines of action a body must take to 
“go across a room”” – esp. given b) the infinite diversity of starting points 
and positions of the body, and c) the infinite diversity of obstacles that may 
lie in the way, and d) the infinite natures and configurations of room 
terrains, and e) the endless combinations of limbs and body positions that may 
be necessary to move from the infinite diversity of starting points.

  The solution lies in the direction of having truly “fluid concepts”  of lines 
of action, with which the body can be fluidly aligned, and proceeding not by 
prior consideration of a set of trajectories (which is absolutely impossible) 
but adventurously “putting your best foot forward” towards the goal, one step 
at a time, and seeing what happens.

  Logan’s formulations lie intuitively in that direction – but they look like 
purely symboiic formulations – whereas internal representations must be 
literally linear in nature. Concepts provide literally “lines of action”  -   
and involve literally “thinking along these lines”.


  From: Piaget Modeler 
  Sent: Sunday, December 16, 2012 4:54 PM
  To: AGI 
  Subject: RE: [agi] Internal Representation


  According to Confucius, Mike Tinter, you are correct.  

  "The person who says it can't be done, and the person who says it can be done 
are both usually correct." ~ Confucius.

  If you want to use some imagination, and figure out how it can be done, then 
by all means.  If you just want to nay say
  and say it can't be done, then that's not helpful.  You must say why it 
cannot be done to be helpful, which you haven't. 

  I think it is already being done, and you simply may not know about it, 
because certain people aren't revealing their 
  results just yet.

  ~PM.



------------------------------------------------------------------------------
  From: [email protected]
  To: [email protected]
  Subject: Re: [agi] Internal Representation
  Date: Sun, 16 Dec 2012 16:06:49 +0000


  “Complexity” is a substitute for thought here. You couldn’t begin to specify 
what are the complex elements here.

  The reality is that living systems can translate these desires/goals, however 
internally represented, into initial actions in a second, and extended courses 
of action in just a few seconds.

  The idea that there is some systematic consideration of sets of sets of 
alternative courses of action and environments  – “sets of sets” because the 
infant/animal could be in an infinite diversity of situations – is quite, quite 
mad, i.e. divorced from any reality whatsoever other than narrow AI programs 
which are incapable of this kind of intelligence and action.

  From: Jim Bromer 
  Sent: Sunday, December 16, 2012 3:09 PM
  To: AGI 
  Subject: Re: [agi] Internal Representation

  On Sun, Dec 16, 2012 at 4:43 AM, Mike Tintner <[email protected]> 
wrote:
  How do the words translate into a physical course of action?

  How do you get from “go” to its first and subsequent movements of limbs? Bear 
in mind, that the same wish – the same formulation – could apply to the infant 
in vastly diverse physical situations - initial physical positions llike lying, 
sitting, lying on side, standing against some object etc - and vastly different 
room configurations.
  ----------------------------

  There is a problem here, but the only true problem is one of complexity.  The 
same problem occurs when the program tries to make sense out of the IO data 
that is input to the program so that it can recognize what kind of situation 
that it is in or responding to.  The problem also occurs when it has to select 
the best kind of reaction to the situation when there are many otions that it 
can select from which are related to the complexities of the situation.  There 
are no  serious problems with implementing general AI other then the complexity 
of these kinds of problems.  A situation can be recognized based on many 
components and there are many 'ideas' (about different kinds of situations) 
that can be recognized based on some of the components that may occur in the 
situation.  It is a many-to-many kind of interpretation problem. Some problems 
are much simpler, but the complications is what makes general AI so complex.
  Jim Bromer

  On Sun, Dec 16, 2012 at 4:43 AM, Mike Tintner <[email protected]> 
wrote:

    Logan,
    You’re thinking of converting words into more words, here?
    How do the words translate into a physical course of action?
    How (i.e. in what forms of representation) would an infant AGI think that 
hadn’t yet learned language, when it say wants to
    “go across the room”...
    crawl, roll, whatever across the carpet to a toy?
    How do you get from “go” to its first and subsequent movements of limbs? 
Bear in mind, that the same wish – the same formulation – could apply to the 
infant in vastly diverse physical situations - initial physical positions llike 
lying, sitting, lying on side, standing against some object etc - and vastly 
different room configurations.
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