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 ---------------------------------------------------------------------- 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 ------------------------------ 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 ------------------------------ 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 ------------------------------ 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-- ------------------------------ 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 ------------------------------ 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 ------------------------------ End of NL-KR Digest *******************