nl-kr-request@CS.ROCHESTER.EDU (NL-KR Moderator Brad Miller) (10/15/88)
NL-KR Digest (10/14/88 18:51:27) Volume 5 Number 18
Today's Topics:
Looking for #<mumble>
Dictionary or Thesaurus
cognitive science text
Model-based Reasoning
Re: common sense "reasoning"
Followup on JMC/Fishwick Diffeq
Re: Newell's response to KL questions
Language Translator (lisp)
Re: Language Translator (lisp)
Submissions: NL-KR@CS.ROCHESTER.EDU
Requests, policy: NL-KR-REQUEST@CS.ROCHESTER.EDU
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Date: Thu, 6 Oct 88 12:56 EDT
From: Sehyo Chang <sec@coby.ics.hawaii.edu>
Subject: Looking for #<mumble>
I am looking for any information regarding 'Mumble' System from
University of Pensylvania, Only reference I have is article from
AAAI-86. Any specific information regarding 'Mumble'(or variant) or how
to get that system would be appeciated. Also, if there are
any public domain text generation system outthere, I would be
very interested.
Sehyo Chang
Software Engineering Lab
sec@coby.ics.hawaii.edu
Thanks
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Date: Fri, 7 Oct 88 09:15 EDT
From: Usenet file
owner <uflorida!mailrus!eecae!cps3xx!usenet@gatech.edu>
Subject: Dictionary or Thesaurus
We are working on a natural language processing program and need an
english dictionary or thesaurus which, for each word, lists the part of
speech of that word. Does anyone know where we can get such a file?
-brian
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Date: Wed, 12 Oct 88 12:20 EDT
From: CAROLG@CC.UTAH.EDU
Subject: cognitive science text
Would anyone who knows of a new cognitive science textbook by Johnson-Laird
please send me the title and publishing information? Thanks.
Carol Georgopoulos
Linguistics Program
University of Utah
carolg@cc.utah.edu
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Date: Tue, 20 Sep 88 19:31 EDT
From: Randall Davis <davis@wheaties.ai.mit.edu>
Subject: Model-based Reasoning
Concerning:
From: jdavis@ucsd.edu (James P. Davis)
Subject: Model-based Reasoning
I am looking for some good references on the subject of Model-based
reasoning (MBR). I am also interested in finding out who is doing
work/research in this area, and what domains are being investigated.
Nobody seems to have put any special compendiums (like Morgan Kaufmann)
in this area yet. Any of you out there?
See the article by Davis and Hamscher in "Exploring AI", a compendium of
recent AAAI survey talks, just published by M/K. The article is a survey of
the state of the art of model-based troubleshooting as of August 1987.
In addition, I'm working on an edited collection of articles summarizing the
MIT group's work in this area, including troubleshooting, test generation,
design, design for testability, combining causal and associational reasoning,
etc. Available in spring/summer 1989.
How does MBR relate to "reasoning from first principles"?
They're used essentially synonymously. "First principles" was used earlier on
to emphasize that the systems reasoned from fundamental engineering principles
rather than empirical associations; "model-based" has been used more recently
to acknowledge the central role of the device model in comparing behavior
predicted by the model with behavior actually emitted by the physical device.
------------------------------
Date: Mon, 26 Sep 88 10:59 EDT
From: John B. Nagle <jbn@glacier.stanford.edu>
Subject: Re: common sense "reasoning"
Use of the term "common-sense reasoning" presupposes that common sense
has something to do with reasoning. This may not be the case. Many animals
exhibit what appears from the outside to be "common sense". Even insects
seem to have rudiments of common sense. Yet at this level reasoning seems
unlikely.
The models of behavior expressed by Rod Brooks and his artificial
insects (there's a writeup on this in the current issue of Omni), and by
Hans Moravec in his new book "Mind Children", offer an alternative. I
won't attempt to summarize that work here, but it bears looking at.
I would encourage workers in the field to consider models of common
sense that don't depend heavily on logic. There are alternative ways to
look at this class of problem. Both Brooks and Moravec use approaches
that are spatial in nature, rather than propositional. This seems to be
a good beginning for dealing with the real world.
The energetic methods Witkin and Kass use in vision processing are
another kind of model which offers a spatial orientation, an internal
drive toward consistency, and the ability to deal with noisy data. These
are promising beginnings for common-sense processing.
John Nagle
------------------------------
Date: Tue, 27 Sep 88 21:21 EDT
From: ceb%ethz.uucp@RELAY.CS.NET
Subject: Followup on JMC/Fishwick Diffeq
>From ceb Wed Sep 28 02:21:09 MET 1988 remote from ethz
>for Robots Interchange
Apropos using diffeqs or other mathematical models to imbue a robot
with the ability to reason about observation of continuous phenomena:
in John McCarthy's message <cdydW@SAIL.Stanford.EDU>, JMC states that
(essentially) diffeqs are not enough and must be imbedded in
"something" larger, which he calls "common sense knowledge". He also
state that diffeqs are inappropriate because "noone could acquire the
initial [boundary?] conditions and integrate them fast enough".
I would like to pursue this briefly, by asking the question:
Just how much of this something-larger (JMC's framework of common
sense knowledge) could be characterized as descriptions
of domains in which such equations are in force, and in describing
the interactions between neighboring domains?
I ask because I observe in my colleagues (and sometimes in myself)
that an undying fascination with the diffeq "as an art form" can lead
one think about them `in vitro', i. e. isolated on paper, with all
those partial-signs standing so proud. You have to admit, the idea as
such gets great mileage: you have a symbolic representation of
something continuous, and we really don't have another good way of
doing this. Notwithstanding, in order to use them, you've got to
describe a domain, the bc's, etc.
This bias towards setting diffeqs up on a stage may also stem from
practical grounds as well: in numerical-analysis work, even having
described the domain and bc's you're not home free yet - the equations
have to be discretized, which leads to huge, impossible-to-solve
matrices, etc. There are many who spend the bulk of their working
lives trying to find discretizations which behave well for certain
ill-behaved but industrially important equations. Such research is
done by trial-and-error, with verification through computer
simulation. In such simulations, to try out new discretizations, the
same simple sample domains are used over and over again, in order to
try to get results which *numerically* agree with some previously
known answer or somebody elses method. In short, you spend a lot of
time tinkering with the equation, and the domain gets pushed to the
back of your mind.
In the case of the robot, two things are different:
1. No one really cares about the numerical accuracy of the results:
something qualitative should be suffficient.
2. The modelled domains are *not* simple, and do not stay the same.
There can also be quite a lot of them.
I would wager that, if the relative importance of modelling the domain
and modelling the intrinsic behavior that takes place within it were
turned around, and given that you could do a good enough job of
modelling the such domains, then:
a. only a very small subset of not scientifically accurate but very
easy to integrate diffeqs would be needed to give good performance,
b. in this case, integration in real time would be a possibility,
and,
c. something like this will be necessary. I believe this supports the
position taken by Fishwick, as near as I understood it.
One might wonder idly if the Navier-Stokes equation (even in laminar
form) would be among the small set of subwager a. Somehow I doubt it,
but this is not really so important, and certainly need not be decided
in advance. It may even be that you can get around using anything at
all close to differential equations.
What does seem important, though, is the need to be able to
geometrically describe domains at least qualitatively accurately, and
this `on the fly'. I am not claiming this would cover all "common
sense knowledge", just a big part of it.
ceb
P. S. I would also be interested to know of anyone working on such
modelling --- this latter preferably by mail.
------------------------------
Date: Fri, 30 Sep 88 00:06 EDT
From: Ashok Goel <goel-a@tut.cis.ohio-state.edu>
Subject: Re: Newell's response to KL questions
I appreciate Professor Allen Newell's explanation of his scheme of
knowledge, symbolic, and device levels for describing the architecture
of intelligence. More recently, Prof. Newell has proposed a scheme
consisting of bands, specifically, the neural, cognitive, rational,
and social bands, for describing the architecture of the mind-brain.
Each band in this scheme can have several levels; for instance, the
cognitive band contains (among others) the deliberation and the
operation levels. What is not clear (at least not to me) is the
relationship between the two schemes. One possible relationship is
colinearity in that the device level corresponds to the neural band,
the symbolic level to the cognitive band, and the knowledge level to
the rational band. Another possibility is containment in the sense
that each of band consists of (the equivalents of) knowledge,
symbolic, and device levels. A yet another possibility is
orthogonality of one kind or another. Which relationship (if any)
between the two schemes does Prof. Newell imply?
A commonality between Newell's two schemes is their emphasis on
structure. A different scheme, David Marr's, focuses on the
processing and functional aspects of cognition. Again, what (if any)
is the relationship between Newell's levels/bands and Marr's levels?
Colinearity, containment, or some kind of orthogonality?
--ashok--
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Date: Thu, 6 Oct 88 08:41 EDT
From: When lispers hack ... the fun begun <m85_miche@tekn01.chalmers.se>
Subject: Language Translator (lisp)
Hello Out there !
Is there by any chance anyone sitting on a source translating some
language to another ?
I've heard that there is some tryings to translate English to
Chinese .... is there any truth in that ?
Which litterature can I seek what I want ?
Thanks for any reply !
/Michel
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Date: Mon, 10 Oct 88 13:26 EDT
From: Mitchell Marks <mitchell@tartarus.uchicago.edu>
Subject: Re: Language Translator (lisp)
In article <227@tekn01.chalmers.se> m85_miche@tekn01.chalmers.se (When lispers hack ... the fun begun) writes:
:Is there by any chance anyone sitting on a source translating some
:language to another ?
:
:I've heard that there is some tryings to translate English to
:Chinese .... is there any truth in that ?
:
:Which litterature can I seek what I want ?
_Computational_Linguistics_ had a couple special issues on machine translation
not too long ago: Vol 11 No. 1 (January-March 1985) and Vol 11 Nos. 2-3 (April-Sept 1985)
with a review article by Jonathan Slocum in the first issue and reports of particular
projects filling out the rest of these issues.
A recent book on this topic is _Machine_Translation:_Theoretical_and_
methodological_issues, ed. Sergei Nirenburg, Cambridge U.P. 1987. The
volume starts with overview articles by Nirenburg and by Allan Tucker,
and contains articles addressing a variety of issues.
-- Mitch Marks
mitchell@tartarus.UChicago.EDU
------------------------------
Date: Mon, 10 Oct 88 18:20 EDT
From: William J. Rapaport <sunybcs!rapaport@rutgers.edu>
Subject: Response to: Language Translator (lisp)
In article <227@tekn01.chalmers.se> m85_miche@tekn01.chalmers.se
>
>Is there by any chance anyone sitting on a source translating some
>language to another ?
>
>Which litterature can I seek what I want ?
There are several sources of info on machine translation. Begin with
"Machine Translation" in S. C. Shapiro (ed.), Encyclopedia of AI (Wiley,
1987).
There are two recent books:
Sergei Nirenburg (ed.), Machine Translation: Theoretical and
Methodological Issues (Cambridge UP, 1987).
and another book by, I think, a fellow named Hutchings, published by
Ellis Horwood, in England; it's a good survey.
There are two major journals:
Computational Linguistics, published by MIT Press for the Association
for Computational Linguistics,
and
Computers and Translation, published by Kluwer Academic Publishers.
William J. Rapaport
Associate Professor
Dept. of Computer Science||internet: rapaport@cs.buffalo.edu
SUNY Buffalo ||bitnet: rapaport@sunybcs.bitnet
Buffalo, NY 14260 ||uucp: {decvax,watmath,rutgers}!sunybcs!rapaport
(716) 636-3193, 3180 ||fax: (716) 636-3464
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End of NL-KR Digest
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