Relay-Version: version B 2.10 5/3/83; site utzoo.UUCP
Path: utzoo!utgpu!water!watnot!watmath!clyde!cuae2!ihnp4!ptsfa!lll-lcc!seismo!rochester!cornell!vax1!czhj
From: czhj@vax1.UUCP
Newsgroups: comp.ai,comp.misc
Subject: Re: Learing about AI
Message-ID: <278@vax1.ccs.cornell.edu>
Date: Thu, 12-Feb-87 12:52:55 EST
Article-I.D.: vax1.278
Posted: Thu Feb 12 12:52:55 1987
Date-Received: Sat, 14-Feb-87 06:44:01 EST
References: <375@atux01.UUCP> <12992@sun.uucp>
Reply-To: czhj@vax1.UUCP (Ted Inoue)
Organization: Cornell Computer Services, Ithaca NY
Lines: 57
Xref: utgpu comp.ai:230 comp.misc:225

In article <12992@sun.uucp> lyang%jennifer@Sun.COM (Larry Yang) writes:
>....
>I was in for a surprise.  Based on my experience, if you want
>to learn about hard-core, theoretical artificial intelligence,
>then you must have a strong (I mean STRONG) background in formal
>logic.  

This is EXACTLY the problem with AI research as it is commonly done today.
(and perhaps yesterday as well).  The problem is that mathematicians, logicians
and computer scientists, with their background in formal logic have no other
recourse than to attack the AI problem using these tools that are available
to them.  Perhaps this is why the field makes such slow progress?

AI is an ENORMOUS problem, to say the least and research into it should not
be bound by the conventional thinking that is going on.  We have to look at
the problem in NEW ways in order to make progress.  I am strongly under the
impression that people with a strict theoretical training will actually HINDER
the field rather than advance it because of the constraints on the ideas that
they come up with just because of their background.

Now, I'm NOT saying that nobody in CS, MATH, or LOGIC is capable of original
thought, however, from much of the research that is being done, and from the
scope of the discussions on the NET, it seems safe to say that many people of
these disciplines discount less formal accounts as frivolous.

But look at the approach that LOGIC gives AI.  It is a purely reductionist
view, akin to studying global plate motion at the level of sub-atomic 
particles.  It is simply the wrong level at which to approach the problem.

A far more RATIONAL approach would be to integrate a number of disciplines
towards the goal of understanding intelligence.  COMPUTER SCIENCE has a major
role because of the power of computer modeling, efficient data structures and
models of efficient parallel computation.  Beyond that, it seems that 
computer science should take a back seat.  LOGIC, well, where would that fit 
in?  Maybe at the very lowest level, but most of that is taken for granted by
computer science.  PHILOSOPHY tends to be a DEAD END, as can clearly be noted
by the arguments going on on the NET :)  Honestly, the philosophy arguments
tend to get so jumbled (though logical), that they really add little to the
field.  COGNITIVE PSYCHOLOGY is a quickly emerging field that is producing some
interesting findings, however, at this stage, it is more descriptive than
anything else.  There is some interesting speculation into the processes that
are going on behind thought in this field, and they should be looked at 
carefully.  However, there is simply so much fluff and pointless experiments
that it takes quite a while to wade through and get anything significant.
LINGUISTICS is a similar field.  The work of Chomsky and others has given us 
some fascinating ideas and may get somewhere in terms of biological constraints
on knowledge and such.  Even NEUROBIOLOGY should get involved.  Reasearch in
this field gives us more insight into internal constraints.  Furthermore,
by studying people with brain disorders (both congenital and through accident)
we can gain some insight into what types of structures are innate or have a
SPECIFIC locus of control.

In sum, I call for using many different disciplines to solve the basic problems
in knowledge, learning and perception.  No single approach will do.


---Ted Inoue