HDTenEightyP/NetNews huggingface dataset:
From: hughes@mercury.cis.udel.edu (John Hughes)
Newsgroups: comp.ai,comp.ai.philosophy
Subject: Re: discussion with Penrose
Date: 22 Dec 92 22:16:13 GMT
Organization: University of Delaware, Newark

In article <1992Dec22.021109.4401@oracorp.com> daryl@oracorp.com (Daryl McCullough) writes:
>The problem with the Turing Test is that there is no precise
>definition of what it means to pass it. However, if one gives a time
>limit for how long the test may go on (say, somewhere between 15
>minutes and 100 years), and one limits the test to purely textual
>exchanges between the judge and the contestant, then it follows that
>whatever the test involves, there exist Turing Machines that can pass
>it.
>
>This is a somewhat controversial point. However, it seems to me that
>it has to be true. There are only finitely many sequences of questions
>that could possibly be asked within the time limit, so all it would
>take in principle to pass it would be a finite lookup table that gave
>an appropriate answer for each question. If you want to include such
>questions as "What time is it?", or "Was it raining yesterday?", then
>you would have to have inputs corresponding to the current time, the
>weather report, etc. As long as the total information needed to answer
>each question is finite, then a lookup table could in principle answer
>it.

This is not so. Though in a finite amount of time there are indeed only a
finite number of questions I can ask, those questions can be chosen from
an infinite set. Your program would have to be able to anticipate any 
legal utterance from the language (and probably several illegal ones), which
is infinitely composable ("Hey computer, do you know Mary? Bill and Joe?
Bob and Ted and Carol and Alice?" etc.). Your program will have to be able
to have a response for an unbounded set of utterances while it has only
finite resources. Your table will have to work by decomposing the utterance
into pieces, and figuring out how the pieces fit together and why. That is,
it will have to understand language. It is not known that there is a Turing
Machine which can do that. 

If what you mean is that there will be exchanges where a properly programmed
TM passes the test by pure luck (i.e. because it just happened to be 
programmed with snappy answers to the exact questions the interrogator asked),
you are quite right; there are many Turing Machines (in fact, many finite state
machines) which will pass many timed Turing Tests. However, I don't think any 
of us can be very happy with that result. If you artificially bound your 
domain, there are TMs (and FSAs) that can do *anything*. They can't learn new
words the interrogator idiosyncratically uses or respond to misconceptions
or even be used in another Turing Test, however, so they would basically be
worthless. 


John
hughes@cis.udel.edu
Newsgroups: comp.ai,sci.math.stat
From: dcohen@paul.rutgers.edu (Dawn Myfanwy Cohen)
Newsgroups: comp.ai
Subject: Re: Admissible Heuristic help
Date: 29 Dec 92 02:05:52 GMT
Distribution: na
Organization: Rutgers Univ., New Brunswick, N.J.

(Jason Leigh) writes:

> If any one can give me a definition, I'd really appreciate it, i.e. what
> does and does not make a heuristic admissible.  And if you know of a book
> where I can find this in, I'd like to know too.

see Nilsson, Principles of Artificial Intelligence, 1980, p.76.

"Let us say  that a search algorithm is  admissible if, for any graph,
it always terminates in an optimal path from s to a goal node whenever
a path from s to a goal node exists."

Now, I think that what you probably have in  mind, given  that you are
talking about "heuristic", is the A* algorithm, which is a variant  on
algorithm A...back up a couple of pages from the above quote.

Algorithm  A is a way  to  search  a  graph.   It  uses  a  notion  of
evaluation functions.  You are  trying to reach a goal node, x, from a
current node, n, having paid a certain price to  get to n,  from start
node s.  You want to  minimize the total cost of getting from s  to x.
That optimum total cost is given by
                    f*(n) = g*(n) + h*(n)
where g*(n) is the cost of getting from s to n and h*(n) is the cost
of getting from n to any goal.  

Now, in general, you have got a handle on g*(n):  you know how much it
has already cost you  to get from s to  n, given that you have already
searched from s to n.   The hard part is figuring out what the optimal
cost of a path from n to any goal node, given that you  don't yet know
where a goal node is in the graph.

This is where heuristics come into the picture.  You can replace h*(n)
with  your  favorite   estimate  (heuristic)  h(n)  for  h*(n).   Now,
depending on  how close your  estimate  of h(n) is  to h*(n), the more
accurate will be your estimate of the total cost of going from s  to x
through  n.  If your estimate  of  the cost is  accurate, then you can
always find an optimal path exactly.  If your estimate of the  cost is
almost accurate, you can probably find  an optimal path exactly (or an
almost optimal path).

However,  if  you use  an  admissible  heuristic,  then,  even if  the
estimate is  not  close, you are still  guaranteed to find an  optimal
path (possibly by  spending a  lot of search time  in identifying  the
path.)   An admissible heuristic is one  that  NEVER OVERESTIMATES the
cost of going from n to  a goal  node.  I.e. h(n) <= h*(n) for every n
in the graph.  You can see Nilsson for a proof.

--Dawn
-- 
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Good Morning!        
--Dawn

Send fan mail to:
uucp:  {ames,bosgd,harvard,moss}!rutgers!paul.rutgers.edu!dcohen
arpa:  dcohen@paul.rutgers.edu
Newsgroups: comp.ai
From: ganesh@icaen.uiowa.edu (Ganesh Tirupattur Ramaseshadri)
Subject: Nexpert/CAD interface
Date: Mon, 28 Dec 1992 18:53:47 GMT
Organization: Iowa Computer Aided Engineering Network, University of Iowa

Hi,

 Is there any way a CAD (preferably UNIGRAPHICS) file can be 
accessed by NEXPERT? 

You can reply to me by mail(sgolla@icaen.uiowa.edu) or on the net.

Thanx in advance.

Satyam

P.S Wishing you all a happy new year.
Newsgroups: comp.ai,sci.math.stat
From: mcclella@yertle.Colorado.EDU (Gary McClelland)
Subject: Re: Learning from subjective data
Organization: University of Colorado, Boulder
Date: Tue, 22 Dec 1992 18:24:03 GMT

bharat@cs.uiuc.edu (R. Bharat Rao) writes:


>almond@statsci.com (Russell G. Almond) writes:
>>R. Bharat Rao (bharat@cs.uiuc.edu) writes:
>>> I was wondering if anyone knew of any work that has been done on
>>> learning from subjective data.  For instance, you may have a data set
>>> of events with a number of independent attribute (x1...xn) and a
>>> single dependent attribute y.  However, y is a subjective rating.

>>This is generally a messy problem and I don't know that there has ever
>>been a definative answer.  I would, however, try the Psych--Stat
>>literature,

I second that recommendation.  You may be particularly interested
in some research on expert judgment by James Shanteau.  He has
studied, among other things, the subjective judgments of
livestock judges and soil experts in agricultural contexts. This
is the same generic problem as your esthetic judgment problem. 
Also of interest would be Ken Hammond's work.  A useful starting
place would be an aritcle in Science by Hammond & Adelman in the
mid 70's.


>OK, the case where you have a unique expert for every problem is
>obviously very messy.  Does the situation become any simpler if each
>expert does many ratings (again no point is rated by more than one
>expert)?  Say, you have 10,000 data points and 500 experts each rate
>20 random points.  Also, for a point you know the expert who rated
>that point.  I think this makes the problem somewhat easier.

Sure, just include terms in your model for the experts.  This
controls for differences among experts so long as the experts
still agree as to which end is up for each attribute.

gary mcclelland
univ of colorado
mcclella@yertle.colorado.edu
Xref: sparky comp.ai:4711 comp.ai.edu:588
From: krebs@faber.faps.uni-erlangen.de (Thomas Krebs)
Newsgroups: comp.ai,comp.ai.edu
Subject: Re: Nexpert/CAD interface
Date: Tue, 29 Dec 1992 08:35:55 GMT
Organization: Institute for Manufacturing Automation, Erlangen, Germany
Distribution: inet
NNTP-Posting-Host: faber.faps.uni-erlangen.de

ganesh@icaen.uiowa.edu (Ganesh Tirupattur Ramaseshadri) writes:

>Hi,

> Is there any way a CAD (preferably UNIGRAPHICS) file can be 
>accessed by NEXPERT? 
I don't understand your interest accessing directly a CAD-file,
because the semantics of those files are normally not documented, as
this is with UNIGRAPHICS.
I think you mean you want to access UNIGRAPHICS data structures. This
you should do with the UFUNC interface. I have done a similar project
with PARASOLID, wich is the (solid) kernel of UNIGRAPHICS and ProKappa
from IntelliCorp. So I think I have some experience in this problem field.
If you want more information please feel free to contact me.
	Thomas
-----------------------------------------------------------------------
Thomas Krebs
Lehrstuhl fuer Fertigungsautomatisierung und Produktionssystematik FAPS
Universitaet Erlangen
Egerlandstrasse 7
8520 Erlangen
Tel.: + 49 9313 85-7964
Fax.: + 49 9313 302528
krebs@faps.uni-erlangen.de
Newsgroups: comp.ai
From: erik@til.com (Erik Horstkotte)
Subject: Re: Learning from subjective data
Reply-To: erik@til.com
Organization: Togai InfraLogic, Inc.
Date: Tue, 22 Dec 1992 18:38:03 GMT

R. Bharat Rao (bharat@cs.uiuc.edu) writes:
> I was wondering if anyone knew of any work that has been done on
> learning from subjective data.  For instance, you may have a data set
> of events with a number of independent attribute (x1...xn) and a
> single dependent attribute y.  However, y is a subjective rating.
>
> For instance, the event could be a work of art and the x's could be
> various nominal/real-valued attribues of the painting.  Then paintings
> in the datasets would be given a grade on (say) beauty (the "y"
> attribute) by a number of different "experts" (whose notions of
> good/bad/indifferent obviously vary wildly).  Each painting would be
> rated only once by a randomly chosen expert (from an arbitrarily large
> pool of experts -- perhaps even a different expert for every
> painting).  

I think that Bart Kosko of USC did some work on Fuzzy Cognitive Maps for 
exactly this kind of ambiguous / contradictory problem.  You might want
to check out his books on neural nets and fuzzy logic to see if he ever
published any of the material.  I know he mentioned it to us verbally
here at TIL.
---
Erik Horstkotte, Togai InfraLogic, Inc.
The World's Source for Fuzzy Logic Solutions (The company, not me!)
erik@til.com, gordius!til!erik - (714) 975-8522
info@til.com for info, fuzzy-server@til.com for fuzzy mail-server

Newsgroups: comp.ai,comp.ai.edu
From: guyyalif@phoenix.Princeton.EDU (Guy Udassin Yalif)
Subject: Expert systems and preliminary airplane design 
Originator: news@nimaster
Keywords: general, learning
Organization: Princeton University
Distribution: inet
Date: Thu, 31 Dec 1992 05:39:45 GMT

I am looking for information about anyone else who may be doing similar
work: I am writing an expert system in CLIPS using all three of its
programming forms: rule-based, object oriented, and procedural. The 
system will, eventually, enable the user to simply input certain 
performance characteristics of the desired plane - and then the code
will produce a plane that satisfies all of the requirements. I have done
a lot of book research for this, but most of it comes from papers that 
are a few years old. If anyone is working on something similar, or has
any tips on working with CLIPS, please contact me. Thanks for the time!
     Guy
guyyalif@phoenix.princeton.edu 
Newsgroups: comp.ai
From: ppc1@cec2.wustl.edu (Peter Pui Tak Chiu)
Subject: MAZE
Organization: Washington University, St. Louis MO
Date: Thu, 24 Dec 1992 07:07:53 GMT

hi everyone,

is there an algorithm to generate maze?  also what are the most popular
algorithm to solve a maze?

please email responses to ppc1@cec1.wustl.edu

thanks in advance

peter
From: rameshag@cs.albany.edu (Anavai G Ramesh)
Newsgroups: comp.ai
Subject: The Next IJCAI Conference.
Date: 29 Dec 92 19:29:33 GMT
Organization: The University at Albany, Comp. Sci. Dept.
Originator: rameshag@odin.albany.edu




Hi,


Does any one know when and where the next IJCAI conference is to be
held.


Thanks
Ramesh
-- 
Anavai G Ramesh               	 
Ph.D. Student , Department of Computer Science	
SUNY at Albany
ramesh@cs.albany.edu
From: heitkoet@lusty.informatik.uni-dortmund.de (Joerg Heitkoetter)
Newsgroups: comp.ai.philosophy
Subject: Of idiots and fools and tools (was: Re: Searle's World and Computers)
Date: 28 Dec 1992 11:16:14 GMT
Organization: CS Department, Dortmund University, Germany
Distribution: world
NNTP-Posting-Host: lusty.informatik.uni-dortmund.de

--

In article <Bznw6n.KJz@iat.holonet.net>, ken@iat.holonet.net (Ken Easlon)
writes:
|> 
|> Taking courses is OK, but not very cost effective.  I would recommend
|> reading a few highly technical articles in each field, and then spending
|> a
|> lot of time thinking about it and figuring out what it really means.
Well, I think you're a bit to hard. If you want to know something about
Physics, it's useless to get the lates Physica-D and start reading, I
would recomment buying Feynman's lectures, as a good staring point.

Just look at children, and how they learn...they don't have highly technical
knowledge of anything, but a disperse knowledge of broad applicability.

They build up "building blocks" (BBs), and later when growing older they
learn how to optimize the recombination of theses building blocks when
the abstract period begins (e.g. supervised learning in school).

Unfortunately when we grow older, the aquisition of such BBs is getting
harder and harder...I thus would recommend to read easy introductory
texts and overview articles, to "grok" the BBs and leave the rest to
the phase you mentioned above with "..lot of time thinking what it
really means.." which I called the optimization period...


I recently showed a video to some non-scientists, which contained
(1) "The 8th day of creation" by Gero von Boehm, a German journalist
who introduced the ideas and interviews with Danny Hillis, Marvin Minsky,
Christof Koch and Jerome Lanier, in contrast to Joseph Weizenbaum.
and
(2) A part of a serial entitled "The machine that changed the world"
a co-production by WBHC(Bosten), BBC(London) and NDR(Hamburg).

The latter showed the complete history of AI, and somwehere compared
expert systems to so called "idiot savants" ("knowing fools"),
persons (like in the 'Rainman' motion picture) that have a very special
knowledge/ability/skill but are completely dumb on any other field.

Afterwards I asked some questions about the "idiot savant", and
strikingly there seemed to be no difference to the casual watcher
between the Profs working in the field of AI and the real (whatever
real means) idiot...

All I wanted to say is "DON'T GET AN IDIOT SAVANT" (there are
too many already...)

BTW: The term "idiot" stems from Greek "idios", which has absolutely
no negative timbre. It just means "someone who is alone with himself".
I see lots of idiots fooling around...(the author not necessarily
excluded ;-)

	-joke

--
Joerg Heitkoetter                        |
Systems Analysis Group                   |  "...for I'm still a child,
University of Dortmund, Germany          |   forever wild.. !"
(joke@ls11.informatik.uni-dortmund.de).  |  -- Fish, contemporary Scottish poet
From: throopw@sheol.UUCP (Wayne Throop)
Newsgroups: comp.ai.philosophy
Subject: Re: causal powers
Date: 22 Dec 92 02:42:21 GMT

:: From: throopw@sheol.uucp (Wayne Throop)
:: Message-ID: <724315603@sheol.UUCP>
:: it seems to me that a good way of looking at 
:: what a program IS, is as a formal description of the causal powers 
:: of a given process running on a computer.

: From: avrom@Csli.Stanford.EDU (Avrom Faderman)
: Message-ID: <1992Dec15.230612.8188@Csli.Stanford.EDU>
: A program CAN BE used as a description of causal powers, but it isn't 
: necessarily.  For example, a program can be used to drive a robot;  this 
: robot can pick things up, put them down, and throw them around.  IF the 
: program is embedded in a robot, it describes these causal powers.

I agree.  In fact, I posted a while back that I agreed with searle that
a program, or even a process instantiating that program, need not have
the "causal powers" of an intelligent entity.  It's just that I think
that Searle's own thought experiment, the Chinese Room, is an example of
a process that DOES have the required causal powers, are programs
instantiated as processes on typical computers. 

( In fairness, it's pretty clear to me that Searle means something
  else by "causal powers" than what I'm calling "effect domain"
  elsewhere in this thread, but honestly, I haven't been able to even
  begin to see where he explains what he DOES mean by the term. )

:: Of course, it may be that some "causal powers" that "meat" brains 
:: have are not computable.  But that's more Penrose's argument than 
:: Searle's.
: Searle would answer that he doesn't claim simply that the causal powers 
: of meat brains are not computable--rather he says that NO causal powers 
: of ANY object are computable:  Computation is a formal process--the 
: same computation can be used to describe any of many causal powers 

I think this is a usage of "not computable" other than that I intended.
I meant it in the formal sense, that is, as it applies to formal
systems, not to concrete processes.

That said, I agree that a formal description of a process with relevant
"causal powers" may also be a formal description of some other process
*without* relevant "causal powers".  But again, I think the processes
Searle chooses to make a concrete example are faulty, and that the CR
and computers *do* have the "right" causal powers. 
--
Wayne Throop  ...!mcnc!dg-rtp!sheol!throopw
Newsgroups: comp.ai.philosophy
From: amdavi@cs.wm.edu (Alexander M. Davis)
Subject: Re: grounding and the entity/environment boundary
Organization: The College of William and Mary
Date: Mon, 28 Dec 1992 14:40:30 GMT

It seems that the usage of phrases along the lines of "the soup
becomes part of me [at time x under certain circumstances]" would
entail loss of that identity under different circumstances. That is,
would one be willing to assert that "At time x, had the soup not been
introduced in such circumstance and therefore not become part of me, I
would not be 'me' since in another circumstance I define 'me' as
having some part integral with this soup."? It all seems to depend on
the conceptual basis of identity: biological entity, behavioral
response network, etc. For AI purposes any one of these models could
be posited. Which is/are being asserted in this discussion?


Alex Davis
amdavi@cs.wm.edu
From: connolly@eeyore.cs.umass.edu (Christopher Ian Connolly)
Newsgroups: comp.ai.philosophy
Subject: Re: The Complexity Required for intelligence
Date: 22 Dec 92 01:24:04 GMT
Organization: University of Massachusetts, Amherst

In article <BzJKxs.1L9@iat.holonet.net>, ken@iat.holonet.net (Ken Easlon) writes:

|> A first pass at digital modeling of emotions would involve the concept of
|> potential fields (see article <BzHnKs.8Bs@iat.holonet.net> subject: The
|> Complexity Required for intelligence).
|> 
|> Generally an emotional state will involve the potential for interaction
|> with another entity.  Thus we must consider not only the potential for
|> change of our own position, but the change of position of the other entity
|> as well.  ...

What you describe is related to a paper which will appear sometime
next year in Biological Cybernetics.  It describes a "potential field"
theory for the operation of the striatum, specifically with regard to
motor control, but since the caudate nucleus and putamen have such
similar structure, it is probably applicable to things like saccades,
sequencing tasks, and emotional state changes:

Connolly CI, Burns JB, A model for the functioning of the striatum.

Your "go juice" could (very roughly speaking) correspond to inhibition
of tonic cholinergic activity in the striatum.  The "stop juice" is a
bit more complicated.  Not an exact fit to what you're saying, but you
might be interested (or at least amused) to flip through it.

						-CC
-- 
	-	-	-	-	-	-	-
Christopher Ian Connolly			connolly@cs.umass.edu
Laboratory for Perceptual Robotics		wa2ifi
University of Massachusetts at Amherst		Amherst, MA 01003
Newsgroups: comp.ai.philosophy
From: jthomas@kolanut.mitre.org (Joe Thomas)
Subject: Re: Self-Reference and Paradox (was Re: Human intelligence...)
Organization: The MITRE Corporation
Date: Tue, 22 Dec 1992 17:05:47 GMT

In article <wa1uVB2w165w@cybernet.cse.fau.edu> tomh@cybernet.cse.fau.edu (Tom  
Holroyd) writes:
> mccolm@darwin.math.usf.edu. (Gregory McColm) writes:
> 
> > Being lazy, I skipped over the logic parts of Penrose's book.  
> > Two logicians I know claim that the logic part is a mess, and 
> > some of the scientific reviews are very negative.  While I 
> > can't comment on the physics (I suspect that he knows what he 
> > is doing there, but I am completely non-expert), I can say that 
> > his discussion on ethology (animal psychology) is uninformed 
> > and decades out of date.
> 
> Flame on.
> 
> Actually, his physics isn't that great either.  He pretty much
> ignores non-equilibrium physics (he sticks to equilibrium thermo-
> dynamics for much of the book, and in one place even calculates
> the probability of the universe based on classical entropy as
> one part in 10**(10**123).  (p.344)  This is a totally absurd number).
> 
> Most phenomena that are mysterious to "classical" (i.e. newtonian)
> physics are well understood in terms of the pattern and structure
> forming properties of systems that are far from equilibrium, which
> includes among other things, us.  When energy flows *through* a
> system, it can self-organize;  this is in contrast with the closed
> systems of classical physics.  The universe may or may not be closed,
> but locally, it is certainly not closed, and most of the physics in
> Penrose's book doesn't apply.

I had a lot of problems with Penrose's book, myself, but I didn't think his  
entropy discussion was that far off (as a non-expert).  Arguments about  
self-organization in open systems don't seem relevant here; what Penrose was  
describing was the low entropy of the _initial_ state of the universe, before  
anything could have self-organized.  

In any case, is your statement that the universe is "certainly not closed"  
meant to imply that energy "flows *through*" the universe from high entropy  
to low entropy the same way it flows through living creatures?  Where does  
the energy come in and go out?  I thought the universe _was_ considered  
closed in this way.

Joe
Newsgroups: comp.ai.philosophy