Path: utzoo!attcan!uunet!tdatirv!sarima
From: sarima@tdatirv.UUCP (Stanley Friesen)
Newsgroups: comp.ai
Subject: Re: What AI is exactly.
Message-ID: <147@tdatirv.UUCP>
Date: 18 Sep 90 21:49:30 GMT
References: <3797@se-sd.SanDiego.NCR.COM> <3543@gara.une.oz.au> <10072@goofy.Apple.COM> <5907@plains.NoDak.edu> <59525@bbn.BBN.COM>
Reply-To: sarima@tdatirv.UUCP (Stanley Friesen)
Organization: Teradata Corp., Irvine
Lines: 38

In article <59525@bbn.BBN.COM> BKort@bbn.com (Barry Kort) writes:
>To my mind, an intelligent system must not only be able to think and solve 
>problems, it must also be able to learn and evolve over time.  The 
>frontiers of learning are the focus of one's interests.  The internal 
>representations of the acquired knowledge (corresponding to our mental 
>models) reflect one's understanding or comprehension.  

	Hmm, this is very interesting.  This may actually be a clue to our
current difficulty in making real progress in AI.  We are trying to add
learning capacity to existing reasoning systems (called expert systems).
Evolution appears to have done it the other way around!  In evolution
*learning* came *first*, and it was only after this was well established
that anything resembling intelligence developed.  Even a planarian shows
the persistant changes of behavior due to prior experience that we define
as learning.

	Perhaps we should scrap all our nifty, complicated reasoning
engines and concentrate on designing a program that does nothing *but*
learn.
>
>Awareness of surroundings gives rise to consciousness.  First, a system 
>needs sensors to gather raw data.  Then it needs to interpret sensory data 
>and integrate it into a structured representation of the external state of 
>affairs.  These representations could be models or frames, or other forms 
>of knowledge representation.

I would say that consciousness requires even more than this.  Most 'higher'
primates, and perhaps many carnivores (like cats) show this kind of
intelligence (awareness of external state using internal mental models, which
can be used to reason).  Consiousness also requires *internal* sensors
which incorporate the entities own state into the internal world models.

>Curiosity is a key emotion of a learning system.  It goes along with 
>related emotions such as interest, fascination, boredom, anxiety, 
>satisfaction, and confidence.

Quite likely, and solving the problem of making a computer curious might well
be a major breakthrough in AI.