How general should be AGI?

When I heard the term AGI for the first time, I had to think about the 
general problem solver from 1959
(http://en.wikipedia.org/wiki/General_Problem_Solver).

It solved a few simple problems but was overstrained with real world
problems.

Second, there is Gödel's theorem which shows that there can not be a complex
machine that 
can can generate both complete and uncontradictory knowledge.

 There is another theorem that shows that 100% AGI is impossible:
Alan Turing proved in 1936 that a general algorithm to solve the halting
problem for 
all possible program-input pairs cannot exist.

On the other hand, we think that AGI is possible because we believe that we
ourselves ARE AGI systems.
But as the theorems show without any doubt: Perfect AGI is impossible.

Of course I am convinced that there can be systems, which are far more
intelligent than humans.
But even these systems will have their limits.

Perhaps further research of our own limits can help us to construct more
intelligent machines.
Perhaps the mechanisms behind human intelligence are so powerful because
they are not designed 
to be a real general problem solver.

Intelligence has a lot to do with recognizing regularities in patterns of
signals which are obtained from the environment.
We can see humans to be very powerful in this ability. But are we real
powerful to recogonize GENERAL regularities???
A simple example shows, that this is by far not the case:

We can recognize very detailed information from the environment 
by our eyes. So we can think, that our optical sense is a general pattern
recognizer. But imagine you would record a soundwave of a speaking man and
visualize the wave on a screen. It would be impossible for you to recognize
the words or even the voice of the person. I am sure that even if you would
practice a child for years with these patterns it would not learn to
understand the voice and sentences. Perhaps a slow and errorful recognition
of some words. But by far not so powerful as our acousthesia.

This shows that our optical sense is not able to recognize general patterns
of our environment. And by the way: The child would not gain conscious
phenomenons like "qualia" when analyzing the sound waves.
Our "optical intelligence pattern recognizer" is NOT AGI. It is narrow AI in
this sense.



Assumption 1:

### Most powerful intelligence and most general intelligence are not
possible at the same time. ###

A system which has most general intelligence will suffer from huge problems
of complexity.
So if we design an architecture which can evolve to very very general
intelligence it will be very very probably need
too many time and memory so that it can be only of theoretical interest.
So one main problem of AGI is to design it general but not too general.
And one of the main questions will be which features and domain knowledge
should be hard coded and how.

If we define intelligence to be the ability to solve complex problems in
complex environments we should ask what 
are adequate limits of complexity. 

Life can only evolve in environments with very narrow conditions.
I think this is similar with intelligence:

Assumption 2:

### Intelligence can work and evolve only in environments with limited
conditions. ###

Nature is very very complex because there are so many particles which
interacts with each other. 
It is important for intelligence, that knowledge of every single particle
and fundamental laws of physics is not necessary to make predictions about
the environment
The change of day and night is an example for a regularity which can be
predicted with high accuracy with very low knowledge of details 
of the environment. In a world with low structure or rapid change of
structure and regularities intelligence is for sure not possible or very
difficult at least.
Our world is a hierarchical world with encapsulated levels. You can see
regularities on high levels without the knowledge of the details below this
level.
This is certainly a key feature of our world without that intelligent life
could not evolve at all.

So I see the following interesting questions for AGI:
What restrictions are adequate or necessary for a practical AGI system to
obtain a good compromise of general and powerful intelligence?
What are the detailed conditions of the environment, that are necessary for
intelligent systems.

-------------------------------------------
agi
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