From LAWS@KL.SRI.COM Tue Dec 15 02:17:52 1987 Mail-From: LAWS created at 19-Nov-86 21:32:08 Date: Wed 19 Nov 1986 21:22-PST From: AIList Moderator Kenneth Laws Reply-To: AIList@SRI-STRIPE.ARPA Us-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025 Phone: (415) 859-6467 Subject: AIList Digest V4 #262 To: AIList@SRI-STRIPE.ARPA Resent-Date: Mon 14 Dec 87 22:42:29-PST Resent-From: Ken Laws Resent-To: isr@vtopus.CS.VT.EDU Resent-Message-Id: <12358590005.16.LAWS@KL.SRI.COM> Status: R AIList Digest Thursday, 20 Nov 1986 Volume 4 : Issue 262 Today's Topics: Conferences - NCAI Exhibit Program & ACM Principles of Database Systems Exhibit Program & AI Papers in Upcoming Simulation Conferences, Journals - IEEE Expert Call For Financial Expert Systems & BBS Call For Commentators in Vision Modeling ---------------------------------------------------------------------- Date: Fri 14 Nov 86 08:42:25-PST From: AAAI Subject: Special Invitation to Universities and Research Institutes The AAAI would like to extend a special invitation to academic institutions and non-profit research laboratories to participate in the Exhibit Program at the Sixth National Conference on Artificial Intelligence, July 14-16, 1987 in Seattle, Washington. It is important to communicate what universities and laboratories are doing and demonstrate your research efforts at the conference. Last year we initiated this new addition was considered one of the highlights of the 1986 conference. AAAI will provide each institution with one 10'x10' booth free, room to describe your demonstration in the Exhibit Guide, and assist with your logistical arrangements. Some direct costs are involved which the AAAI cannot provide assistance with. Those costs include shipping equipment to the site, telephone lines (communication (required) or computer), housing, and others. We can direct interested groups to vendors who may be able to assist with equipment needs. Last year, many hardware vendors donated equipment for the university demonstrations and will continue with this practice next year. We hope you can join us in Seattle and help disseminate the latest research results to our conference attendees. If you or your department are interested in participating, please contact: Steven Taglio AAAI 445 Burgess Drive Menlo Park, CA 94025 (415) 328-3123 AAAI-Office@sumex-aim.arpa ------------------------------ Date: Thu, 13 Nov 86 22:39:02 PST From: Moshe Vardi Subject: ACM Symp. on Principles of Database Systems THE SIXTH ACM SYMPOSIUM ON PRINCIPLES OF DATABASE SYSTEMS Call for Exhibits The Sixth ACM Symposium on Principles of Database Systems will take place between March 23 and March 25, 1987, at the Bahia Resort Hotel in San Diego. The symposium will cover new develop- ments in both theoretical and practical aspects of database and knowledge-based systems. Previous symposia have been attended by researchers from both industry and academia. For the first time, this year the symposium will include exhibits of state-of-the-art products from industry. If you have a product you would like to exhibit, please send a brief description by December 15, 1986, to: Victor Vianu Local Arrangements Chairman, PODS '87 EECS Department, MC-014 Univ. of California at San Diego La Jolla, California 92093 (619) 534-6227 vianu@sdcsvax.ucsd.edu Since space is limited, exhibits will be selected based on the proposals received. Your contribution would be greatly appreciat- ed. ------------------------------ Date: WED, 10 oct 86 17:02:23 CDT From: leff%smu@csnet-relay Subject: AI at upcoming conferences (simulation) 1987 Society for Computer Simulation Multiconference 1987 Modeling and Simulation on Microcomputers Individual Face Classification by Computer Vision Robert A. Campbell, Scott Cannon, Greg Jones, Neil Morgan, Utah State University AI and Simulation Preliminary Screening of Wastewater Treatment Alternatives Using Personal Consultant Plus Giles G. Patry, Bruce Gall, McMaster University The impact of embedding AI tools in a control system simulator Norman R. Nielson SRI International An Expert System for the Controller James A. Sena, L. Murphy Smith,Texas A&M University Application of Artificial Intelligence Techniques to Simulation Pauline A. Langen, Carrier Corporation The Expert System Applicability Question Louis R. Gieszi An Intelligent Interface for Continuous System Simulation Wanda M. ustin The Aerospace Corporation Behrokh Khoshnevis University of Southern California Logic Progrmming and Discrete Event Simulation Robert G. Sargent, Ashvin, Radiya, Syracuse University Expet Systems for Interactive Simulation of Computer System Dynamics Axel Lehmann, University of Karlsruhe An Automated Simulation Modeling System Based on AI Techniques Behrokh Khoshnevis, An-Pin Chen, University of Southern California Design of a Flexible Extendible Modeling Environment Robert J. Pooley University of Edinburgh Prolog for Simulation Expert System Shell with System Simulation Capabilities Ivan Futo, Computer Research Institute Languages for Distributed Simulation Brian Unger, Xining Li, University of Calgary Process Oriented Simulation in Prolog Jeans Vaucher, University of Montreal Application of Artificial Intelligence Techniques to Simulation Pauline A. Langen, Carrier Corporation Computer Integrated Manufacturing Systems and robotics A Data Modeling Approach to Improve System's Intelligence in Automated Manufacturing Lee-Eng Shirley Lin, Yun-Baw Lin, Tamkang University KARMA - A Knowledge-Based Robot Manipulation Graphics Simulation Richard H. Kirschbrown, Consultant Development of questions-answers simulator for real-time scheduling and control in flexible manufacturing system using Prolog Lee-Eng Shirley Lin, Tamkang Unviersity, Chang Yung Lui, National Sun Yat-Sen University Simulation of uncertainty and product structure in MRP Louis Brennan, Surendra Mohan Gupta, Northeastern University __________________________________________________________________________ The University of ARizona Fourth Symposium on Modeling and Simulation Methodology January 19-23 1987 AI and Simulation I, R. V. Reddy AI and Simulation II, B. P. Zeigler (Object Oreinted/AI Programming, Combining Discrete Event and Symbolic Models, Hierarchical, Modular Modelling/Multiprocessor Simulation) AI and Simulation III, T. I. Oren cognizant Simulation Systems, AI and Quality Assurance Methodology AI and Simulation IV Environments for AI and Simulation, Interfacing Lisp Machines and Simulation Engines Special Sessions on Model-basedDiagnosis and Expert Systems Training, Inductive Modelling, Goal Directed, Variable-Structure Models, AI and Simulation in Education ------------------------------ Date: 12 November 1986, 09:48:28 EST From: "Chidanand V. Apte" Subject: Call for Papers - Financial Expert Systems (IEEE Expert) CALL FOR PAPERS --------------- IEEE EXPERT Special Issue - Fall 1987 AI Applications in Financial Expert Systems The Fall 1987 issue of IEEE EXPERT will be devoted to papers that discuss the technical requirements imposed upon AI techniques for building intelligent systems for financial applications and the methodologies employed for the construction of such systems. Requirements for submission of papers ------------------------------------- Authors should submit their papers to the guest editors no later than APRIL 1, 1987. Each submission should include one cover page and five copies of the complete manuscript. The one cover page should include Name(s), affiliation(s), complete address(es), identification of principal author and telephone number. The five copies of the complete manuscript should each include: Title and abstract page: title of paper, 100 word abstract indicating significance of contribution, and The complete text of the paper in English, including illustrations and references, not exceeding 5000 words. Topics of interest ------------------ Authors are invited to submit papers describing recent and novel applications of AI techniques in the research and development of financial expert systems. Topics (in the context of the domain) include, but are not limited to: Automated Reasoning, Knowledge Representations, Inference Techniques, Problem Solving Control Mechanisms, Natural Language Front Ends, User Modeling, Explanation Methodologies, Knowledge Base Debugging, Validation, and Maintenance, and System Issues in Development and Deployment. Guest Editors -------------- Chidanand Apte (914-945-1024, Arpa: apte@ibm.com) John Kastner (914-945-3821, Arpa: kastner@ibm.com) IBM Thomas J. Watson Research Center P.O. Box 218 Yorktown Heights, New York 10598 ======== ------------------------------ Date: Wed, 19 Nov 86 13:26:38 est From: princeton!mind!harnad@seismo.CSS.GOV (Stevan Harnad) Subject: Modeling vision: A call for commentators. Keywords: connectionism, neural modeling, vision, robotics, neuroethology This is an experiment in using the Net to find eligible commentators for articles in the Behavioral and Brain Sciences (BBS), an international, interdisciplinary journal of "open peer commentary," published by Cambridge University Press, with its editorial office in Princeton NJ. The journal publishes important and controversial interdisciplinary articles in psychology, neuroscience, behavioral biology, cognitive science, artificial intelligence, linguistics and philosophy. Articles are rigorously refereed and, if accepted, are circulated to a large number of potential commentators around the world in the various specialties on which the article impinges. Their 1000-word commentaries are the co-published with the target article as well as the author's response to each. The commentaries consist of analyses, elaborations, complementary and supplementary data and theory, criticisms and cross-specialty syntheses. Commentators are selected by the following means: (1) BBS maintains a computerized file of over 3000 BBS Associates; the size of this group is increased annually as authors, referees, commentators and nominees of current Associates become eligible to become Associates. Many commentators are selected from this list. (2) The BBS editorial office does informal as well as formal computerized literature searches on the topic of the target articles to find additional potential commentators from across specialties and around the world who are not yet BBS Associates. (3) The referees recommend potential commentators. (4) The author recommends potential commentators. We now propose to add the following source for selecting potential commentators: The abstract of the target article will be posted in the relevant newsgroups on the net. Eligible individuals who judge that they would have a relevant commentary to contribute should contact me at the e-mail address indicated at the bottom of this message, or should write by normal mail to: Stevan Harnad Editor Behavioral and Brain Sciences 20 Nassau Street, Room 240 Princeton NJ 08542 "Eligibility" usually means being an academically trained professional contributor to one of the disciplines mentioned earlier, or to related academic disciplines. The letter should indicate the candidate's general qualifications as well as their basis for wishing to serve as commentator for the particular target article in question. It is preferable also to enclose a Curriculum Vitae. (This self-nomination format may also be used by those who wish to become BBS Associates, but they must also specify a current Associate who knows their work andis prepared to nominate them; where no current Associate is known by the candidate, the editorial office will send the Vita to approporiate Associates to ask whether they would be prepared to nominate the candidate.) BBS has rapidly become a highly read read and very influential forum in the biobehavioral and cognitive sciences. A recent recalculation of BBS's "impact factor" (ratio of citations to number of articles) in the American Psychologist [41(3) 1986] reports that already in its fifth year of publication BBS's impact factor had risen to become the highest of all psychology journals indexed as well as 3rd highest of all 1300 journals indexed in the Social Sciences Citation Index and 50th of all 3900 journals indexed in the Science Citation index, which indexes all the scientific disciplines. The following is the abstract of the second forthcoming article on which BBS invites self-nominations by potential commentators. (Please note that the editorial office must exercise selectivity among the nominations received so as to ensure a strong and balanced cross-specialty spectrum of eligible commentators.) ----- NEUROETHOLOGY OF RELEASING MECHANISMS: PREY-CATCHING IN TOADS Joerg-Peter Ewert Neuroethology Department, FB 19, University of Kassel D-3500 Kassel Federal Republic of Germany ABSTRACT: "Sign stimuli" elicit specific patterns of behavior when an organism's motivation is appropriate. In the toad, visually released prey-catching involves orienting toward the prey, approaching, fixating and snapping. For these action patterns to be selected and released, the prey must be recognized and localized in space. Toads discriminate prey from nonprey by certain spatiotemporal stimulus features. The stimulus-response relations are mediated by innate releasing mechanims (RMS) with recognition properties partly modifiable by experience. Striato-pretecto-tectal connectivity determines the RM's recognition and localization properties whereas medialpallio-thlamo-tectal cicuitry makes the system sensitive to changes in internal state and to prior history of exposure to stimuli. RMs encode the diverse stimulus conditions involving the same prey object through different combinations of "specialized" tectal neurons, involving cells selectively tuned to prey features. The prey-selective neurons express the outcome of information processing in functional units consisting of interconnected cells. Excitatory and inhibitory interactions among feature-sensitive tectal and pretectal neurons specify the perceptual operations involved in distinguishing prey from its background, selecting its features, and discriminating it from predators. Other connections indicate stimulus location. The results of these analyses are transmitted by specialized neurons projecting from the tectum to bulbar/spinal motor systems, providing a sensorimotor interface. Specific combinations of projective neurons -- mdiating feature- and space-related messages -- form "command releasing systems" that activate corresponding motor pattern generators from appropriate prey-catching action patterns. ----- Potential commentators should send their names, addresses, a description of their general qualifications and their basis for seeking to comment on this target article in particular to the address indicated earlier or to the following e-mail address: Stevan Harnad {allegra, bellcore, seismo, rutgers, packard} !princeton!mind!harnad harnad%mind@princeton.csnet (609)-921-7771 ------------------------------ End of AIList Digest ******************** From LAWS@KL.SRI.COM Tue Dec 15 02:20:51 1987 Mail-From: LAWS created at 19-Nov-86 21:38:55 Date: Wed 19 Nov 1986 21:37-PST From: AIList Moderator Kenneth Laws Reply-To: AIList@SRI-STRIPE.ARPA Us-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025 Phone: (415) 859-6467 Subject: AIList Digest V4 #263 To: AIList@SRI-STRIPE.ARPA Resent-Date: Mon 14 Dec 87 22:42:32-PST Resent-From: Ken Laws Resent-To: isr@vtopus.CS.VT.EDU Resent-Message-Id: <12358590014.16.LAWS@KL.SRI.COM> Status: R AIList Digest Thursday, 20 Nov 1986 Volume 4 : Issue 263 Today's Topics: Philosophy - D/A Distinction and Symbols & Machine Intelligence/Consciousness & Philosophy of Mind Stuff ---------------------------------------------------------------------- Date: 12 Nov 86 18:01:31 GMT From: trwrb!aero!marken@ucbvax.Berkeley.EDU (Richard Marken) Subject: D/A Distinction and Symbols In article <3490001@hpfcph.HP.COM> Bob Myers makes an eloquent debut to the D/A distinction debate with the following remarks: >The difference between "analog" and "digital" is nothing more than the >difference between a table of numbers and the corresponding graph; in a >digital representation, we assign a finite-precision number to indicate the >value of something (usually a signal) at various points in time (or frequency, >or space, or whatever). An "analog" representation is just that - we choose >to view some value (voltage, current, water pressure, anything) as hopefully >being a faithful copy of something else. An excellent example is a >microphone, which converts a varying pressure into an "analogous" signal - >a varying voltage. This distinction has nothing to do with the accuracy of >the representation obtained, the technology used to obtain, or any of a host >of other items that come to mind when we think of the terms "analog" and >"digital". We haven't heard for some time from the usually prolific Dr. Har- nad, who started the debate with a request for definitions of the A/D distinction. It seems to me that the topic was broached in the first place because Harnad had some notion that "analog" or "non-symbolic" robots are, in some way, a better subject for a test of machine intelligence (a la Turing) than the"symbol manipula- tor" envisioned by Turing himself. Whether this was where Harnad was going or not, I would like to make one point. It seems to me, based on the cogent A/D distinc- tion made by Myers, that both analog and digital representations are "symbolic". In both cases, some variable (number, signal lev- el) is used to represent another. The relationship between the variables is _arbitrary_ in, potentially, two ways: 1) the nature of the analog signal or number used to represent the other variable is arbitrary- other types of signals or other number values could have also been used. Using electri- city to represent sound pressure level is arbitrary (though, possibly, a good enginnering decision)-- sound pressure level could have been represented by height of a needle (hey, it is) or by water pressure or whatever. 2) the values of the analog (or digital) variable used to represent the values of another variabl are, in principle, also arbi- trary. Randomly different voltages could be used to represent different sound pressure levels. This would be difficult (and possibly ridiculous) to try to implement but it could be done (like where changes over time in the variable being represented are very slow). Maybe the best way to put this is as follows: in digital or analog representation we have some variable, y,that represents some other, x, so that y= f(x). Regardless of the analog or digital characteristics of x and y, y "symbolizes" x because 1) another variable, y', could be used to represent x (so y is arbitrary) and 2) y could be defined by a different function, f', so f is arbitrary. I think 1) and 2) capture what is meant when it is said that symbols are arbitrary representations of events. Symbols are not completely arbitrary. Once y and f are selected you've got to stick with them (in the context of your application) or the symbol system is useless. Thus, the sounds that we use to represent events (f) and the fact that we use sounds (y) is an arbitrary propery of our language symbol system. But now that we've settled on it we've got to stick with it for it to be useful (for communication). We could (like humpty-dumpty) keep changing the relationship between words and events but this kind of arbitrariness would make communication impossible. Conclusion: I don't believe that the A/D distinction is a distinction between non-symbol vs symbol systems. If there is a difference between robots (that deal with "real world" variables) and turing machines (that deal with artificial symbol systems) I don't believe it can turn on the fact that one deals with symbols and the other doesn't. They both deal with symbols. So what is the difference? I think there is a difference between robots (of certain types) and turing machines-- and a profound one at that. But that's another posting. -- Disclaimer-- The opinions expressed are my own. My employer, mother wife and teachers should not be held responsible -- though some tried valiantly to help. Richard Marken Aerospace Corp. (213) 336-6214 Systems Simulation and Analysis P.O. Box 92957 M1/076 Los Angeles, CA 90009-2957 marken@aero.ARPA kk ------------------------------ Date: Fri, 7 Nov 86 15:31:31 +0100 From: mcvax!ukc!rjf@seismo.CSS.GOV Subject: Re: machine intelligence/consciousness There has been some interesting discussion (a little while back now) on the possibility of 'truly' intelligent machines; in particular the name of Nagel has been mentioned, and his paper 'What is it like to be a bat?'. This paper is not, however, strictly relevant to a discussion of machine intelligence, because what Nagel is concerned with is not intelligence, but consciousness. That these are not the same, may be realised on a little contemplation. One may be most intensely conscious while doing little or no cogitation. To be intelligent - or, rather, to use intelligence - it seems necessary to be conscious, but the converse does not hold - that to be conscious it is necessary to be intelligent. I would suggest that the former relationship is not an necessary one either - it just so happens that we are both conscious and (usually) intelligent. Animals probably are conscious without being intelligent. Machines may perhaps be intelligent without being conscious. If these are defined seperately, the problem of the intelligent machine becomes relatively trivial (though that may seem too good to be true): an intelligent machine is capable of doing that which would require intelligence in a person, eg high level chess. On the other hand, it becomes obvious that what really exercises the philosophers and would-be philosophers (I include myself) is machine consciousness. As for that: Another article in the same collection by Nagel (Mortal Questions, 1978) takes his ideas on consciousness somewhat further. A summary of the arguments developed in 'Subjective and Objective' could not possibly do them justice (anyone interested is heartily recommended to obtain a copy), so only the conclusions will be mentioned here. Briefly, Nagel views subjectivity as irreducible to objectivity, indeed the latter derives from the former, being a corrected and generalised version of it. A maximally objective view of the world must admit the reality of subjectivity, in the minimal sense that individuals do hold differing views, and there is no better - or worse - judge of which view is more truly objective, than another individual. This view does not to any extent denigrate the practicality of objective methods (the hypothesis of objective reality is proven by the success of the scientific method), but nor is it possible to deny the necessity of subjectivity in some situations, notably those directly involving other people. It is surely safe to say that no new objective method will ever substitute for human relationships. And the reason that subjectivity works in this context is because of what Nagel terms 'intersubjectivity' - individuals identifying with each other - using their imaginations creatively and for the most part accurately to put themselves in another person's shoes. So what, really, is consciousness? According to Nagel, a thing is conscious if and only if it is like something to be that thing. In other words, when it may be the subject (not the object!) of intersubjectivity. This accords with Minsky (via Col. Sicherman): 'consciousness is an illusion to itself but a genuine and observable phenomenon to an outside observer...' Consciousness is not self-consciousness, not consiousness of being conscious, as some have thought, but is that with which others can identify. This opens the way to self-awareness through a hall of mirrors effect - I identify with you identifying with me... And in the negative mode - I am self-conscious when I feel that someone is watching me. It may perhaps be supposed that the concept of consciousness evolved as part of a social adaptation - that those individuals who were more socially integrated, were so at least in part because they identified more readily, more intelligently and more imaginatively with others, and that this was a successful strategy for survival. To identify with others would thus be an innate behavioural trait. So consciousness is at a high level (the top?) in software, and is, moreover, not supported by a single unit of hardware, but by a social network. In its development, at least. I, or anyone else, might suppose that I am still conscious when alone, but not without (the supposer, whether myself or another) having become conscious in a social context. When I suppose myself to be conscious, I am imagining myself outside myself - taking the point of view of an (hypothetical) other person. An individual - man or machine - which has never communicated through intersubjectivity might, in a sense, be conscious, but neither the individual nor anyone else could ever know it. A community of machines sufficiently sophisticated that they identify with each other in the same way as we do, may some day develop, but how could we decide whether they were really conscious or not? They might know it, but we never could - and that is neither pessimism not prejudice, but a matter of principle. Subjectively, we all know that consciousness is real. Objectively, we have no reason to believe in it. Because of the relationship between subjectivity and objectivity, that position can never be improved on. Pragmatism demands a compromise between the two extremes, and that is what we already do, every day, the proportion of each component varying from one context to another. But the high-flown theoretical issue of whether a machine can ever be conscious allows no mere pragmatism. All we can say is that we do not know, and, if we follow Nagel, that we cannot know - because the question is meaningless. (Technically, the concept of two different but equally valid ways of seeing, in this case subjectively and objectively, is a double aspect theory; the dichotomy lies not in the nature of reality, but in our perception. Previous double aspect theories, interestingly consistent with this one, have been propounded by Spinoza - regarding our perception of our place within nature - and Strawson - on the concept of a person. I do not have the full references to hand.) Any useful concepts among those foregoing probably derive from Nagel, any misleading ones from myself; none from my employers. Rob Faichney ------------------------------ Date: 18 Nov 86 08:30:00 EST From: "CUGINI, JOHN" Reply-to: "CUGINI, JOHN" Subject: philosophy of mind stuff (get it?) Can't resist a few more go-rounds with S. Harnad. Lest the size of these messages increase exponentially, I'll try to avoid re-hashing old issues and responding to side-issues... > Harnad: > I agree that scientific inference is grounded in observed correlations. > But the primary correlation in this special case is, I am arguing, between > mental states and performance. That's what both our inferences and our > intuitions are grounded in. The brain correlate is an additional cue, but only > inasmuch as it agrees with performance. > ...in ambiguous > cases, behavior was and is the only rational arbiter. Consider, for > example, which way you'd go if (1) an alien body persisted in behaving like a > clock-like automaton in every respect -- no affect, no social interaction, > just rote repetition -- but it DID have something that was indistinguishable > (on the minute and superficial information we have) from a biological-like > nervous system), versus (2) if a life-long close friend of yours had > to undergo his first operation, and when they opened him up, he turned > out to be all transistors on the inside. I don't set much store by > this hypothetical sci-fi stuff, especially because it's not clear > whether the "possibilities" we are contemplating are indeed possible. But > the exercise does remind us that, after all, performance capacity is > our primary criterion, both logically and intuitively, and its > black-box correlates have whatever predictive power they may have > only as a secondary, derivative matter. They depend for their > validation on the behavioral criterion, and in cases of conflict, > behavior continues to be the final arbiter. I think I may have been tactitly conceding the point above, which I now wish to un-concede. Roughly speaking, I think my (everyone's) epistemological position is as follows: I know I have a mind. In order to determine if X has a mind I've got to look for analogous external things about X which I know are causally connected with mind in *my own* case. I naively know (and *how* do I know this??) that large parts of my performance are an effect of my mind. I scientifically know that my mind depends on my brain. I can know this latter correlation even *without* performance correlates, eg, when the dentist puts me under, I can directly experience my own loss of mind which results from loss of whatever brain activity. (I hope it goes without saying that all this knowledge is just regular old reliable knowledge, but not necessarily certain - ie I am not trying to respond to radical skepticism about our everyday and scientific knowledge, the invocation of deceptive dentists, etc.) I'll assume that "mind" means, roughly, "conscious intelligence". Also, assume throughout of course that "brain" is short-hand for "brain activity known (through usual neuro-science techniques) to be necessary for consciousness". Now then, armed with the reasonably reliable knowledge that in my own case, my brain is a cause of my mind, and my mind is a cause of my performance, I can try to draw appropriate conclusions about others. Let's take 4 cases: 1. X1 has brains and performance - ie another normal human. Certainly I have good reason to assume X1 has a mind (else why should similar causes and effects be mediated by something so different from that which mediates in my own case?) 2. X2 has neither brains nor performance - and no mind. 3. X3 has brains, but little/no performance - eg a case of severe retardation. Well, there doesn't seem much reason to believe that X has intelligence, and so is disqualified from having mind, given our definition. However, it is still reasonable to believe that X3 might have consciousness, eg can feel pain, see colors, etc. 4. X4 has normal human cognitive performance, but no brains, eg the ultimate AI system. Well, no doubt X4 has intelligence, but the issue is whether X4 has consciousness. This seems far from obvious to me, since I know in my own case that brain causes consciousness causes performance. But I already know, in the case of X4, that the causal chain starts out at a different place (non-brain), even if it ends up in the same place (intelligent performance). So I can certainly question (rationally) whether it gets to performance "via consciousness" or not. If this seems too contentious, ask yourself: given a choice between destroying X3 or X4, is it really obvious that the more moral choice is to destroy X3? Finally, a gedanken experiment (if ever there was one) - suppose (a la sci-fi stories) they opened you up and showed you that you really didn't have a brain after all, that you really did have electronic circuits - and suppose it transpired that while most humans had brains, a few, like yourself, had electronics. Now, never doubting your own consciousness, if you *really* found that out, would you not then (rationally) be a lot more inclined to attribute consciousness to electronic entities (after all you know what it feels like to be one of them) than to brained entities (who knows what, if anything, it feels like to be one of them?)? Even given *no* difference in performance between the two sub-types? Showing that "similarity to one's own internal make-up" is always going to be a valid criterion for consciousness, independent of performance. I make this latter point to show that I am a brain-chauvinist *only insofar* as I know/believe that I *myself* am a brained entity (and that my brain is what causes my consciousness). This really doesn't depend on my own observation of my own performance at all - I'd still know I had a mind even if I never did any (external) thing clever. To summarize: brainedness is a criterion, not only via the indirect path of: others who have intelligent performance also have brains, ergo brains are a secondary correlate for mind; but also via the much more direct path (which *also* justifies performance as a criterion): I have a mind and in my very own case, my mind is closely causally connected with brains (and with performance). > As to CAUSATION -- well, I'm > sceptical that anyone will ever provide a completely satisfying account > of the objective causes of subjective effects. Remember that, except for > the special case of the mind, all other scientific inferences have > only had to account for objective/objective correlations (and [or, > more aptly, via) their subjective/subjective experiential counterparts). > The case under discussion is the first (and I think only) case of > objective/subjective correlation and causation. Hence all prior bets, > generalizations or analogies are off or moot. I agree that there are some additional epistemological problems, compared to the usual cases of causation. But these don't seem all that daunting, absent radical skepticism. We already know which parts of the brain correlate with visual experience, auditory experience, speech competence, etc. I hardly wish to understate the difficulty of getting a full understanding, but I can't see any problem in principle with finding out as much as we want. What may be mysterious is that at some level, some constellation of nerve firings may "just" cause visual experience, (even as electric currents "just" generate magnetic fields.) But we are always faced with brute-force correlation at the end of any scientific explanation, so this cannot count against brain-explanatory theory of mind. > Perhaps I should repeat that I take the context for this discussion to > be science rather than science fiction, exobiology or futurology. The problem > we are presumably concerned with is that of providing an explanatory > model of the mind along the lines of, say, physics's explanatory model > of the universe. Where we will need "cues" and "correlates" is in > determining whether the devices we build have succeeded in capturing > the relevant functional properties of minds. Here the (ill-understood) > properties of brains will, I suggest, be useless "correlates." (In > fact, I conjecture that theoretical neuroscience will be led by, rather > than itself leading, theoretical "mind-science" [= cognitive > science?].) In sci-fi contexts, where we are guessing about aliens' > minds or those of comatose creatures, having a blob of grey matter in > the right place may indeed be predictive, but in the cog-sci lab it is > not. Well, I plead guilty to diverting the discussion into philosophy, and as a practical matter, one's attitude in this dispute will hardly affect one's day-to-day work in the AI lab. One of my purposes is a kind of pre-emptive strike against a too-grandiose interpretation of the results of AI work, particularly with regard to claims about consciousness. Given a behavioral definition of intelligence, there seems no reason why a machine can't be intelligent. But if "mind" implies consciousness, it's a different ball-game, when claiming that the machine "has a mind". My as-yet-unarticulated intuition is that, at least for people, the grounding-of-symbols problem, to which you are acutely and laudably sensitive, inherently involves consciousness, ie at least for us, meaning requires consciousness. And so the problem of shoehorning "meaning" into a dumb machine at least raises the issue about how this can be done without making them conscious (or, alternatively, how to go ahead and make them conscious). Hence my interest in your program of research. John Cugini ------------------------------ End of AIList Digest ******************** From LAWS@KL.SRI.COM Tue Dec 15 02:22:30 1987 Mail-From: LAWS created at 19-Nov-86 21:45:21 Date: Wed 19 Nov 1986 21:43-PST From: AIList Moderator Kenneth Laws Reply-To: AIList@SRI-STRIPE.ARPA Us-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025 Phone: (415) 859-6467 Subject: AIList Digest V4 #264 To: AIList@SRI-STRIPE.ARPA Resent-Date: Mon 14 Dec 87 22:42:34-PST Resent-From: Ken Laws Resent-To: isr@vtopus.CS.VT.EDU Resent-Message-Id: <12358590022.16.LAWS@KL.SRI.COM> Status: R AIList Digest Thursday, 20 Nov 1986 Volume 4 : Issue 264 Today's Topics: Reviews - Spang Robinson Report & Recent Press Releases, Open House - Invitation to USC AI & VLSI Demo, Seminar - Trajectory Planning in Time-Varying Environments (MIT) & An Expert System for Building Layout (CMU) & New Paths in Knowledge Engineering (BBN) ---------------------------------------------------------------------- Date: WED, 10 oct 86 17:02:23 CDT From: leff%smu@csnet-relay Subject: Spang Robinson Report Summary Spang Robinson Report, November 1986 Vol 2, No 11 __________________________________________________________________________ Discussion of AI Applications to Manufacturing Carnegie Group has 90 percent of their toolkit sales and 100- per cent of their custom contracts from manufacturing clients. A spin off from Composition Systems is selling tools to manufacturing customers. (Composition Systems sells an expert system for newspaper layout [LEFF]) The Society of Manufacturing Engineers has formed an AI in Manufacturing Advisory Committee (contact Michael Tew 313 271-1500). Allen Bradley will have "knowledge base technologies" in their line of factory controllers. __________________________________________________________________________ Software Review of Knowledge Craft __________________________________________________________________________ California Intelligence is selling products that add frame and blackboard facilities to EXSYS, FRAME and TABLET respectively. They can also be used with other AI tools and even to mix AI tools with other applications. TABLET also allows the addition of variables to expert systems that do not have them. FRAME will call an outside program when the value of the slot is needed. __________________________________________________________________________ Other Material: Nihol Life, Japan, is developing an expert system that will assess the insurability of people with various medical conditions. Boeing has a Knowledge-Based System Center in Japan that provides info to various companies operating in Japanese, both American and Japan Fujitsu is including an expert system to help choose algorithms for image processing with its general purpose image processing system. Fujitsu will be selling an AI tool for its 68010 based engineering work station. Intellicorp will be entering the Japanese market on its own when its contract with CSK expires this November. SRI Cambridge will be organizing a multi-million dollar natural language effort in England. __________________________________________________________________________ BOOKs Reviewed Portraits of Success: Impressions of Silicon Valley by Carolyn Caddes On Machine Intelligence by Donald Michie ------------------------------ Date: WED, 10 oct 86 17:02:23 CDT From: leff%smu@csnet-relay Subject: summary of recent press releases >From the report on the IEEE Annual Briefing for the Media James A. Sprowl of the Illinois Institute of Technology is developing an auotmated client interviewing and legal document assembly system which automated wills, contracts, pleadings and others. It is designed to assist nonspecialized attorneys. __________________________________________________________________________ Robert L. Degenhart AT&T Bell Labs, 201 - 564-4091 Bell Labs has developed an IC chip containing 256 electronic neurons. It contains 25,000 transistors, 100,000 resistors on 1/4 square inch of silicon. Retrieval speed is 400 nanoseconds and anticipate their use in image processors. Neural networks permit greater chip density and require fewer layers of lithography. They have been able to fabricate chips with one tenth of a micron features. __________________________________________________________________________ >From Lisp Machine Inc They have marketing TI's Explorer along with PICON a real-time expert system application package and IKE, a consultation style expert system. PICON achieves 200 rule frames/seconds in 2000 rule systems. They project 1000 rule frames/second in 10,000 rule systems by the end of 1987. __________________________________________________________________________ >From Knowledge Engineering, 274 West 12th Street, PO Box 366, Village Station, New York, New YOrk 10014-0366 They are marketing a review of AI market resources for $47.50. They also publish a Knowledge Engineering Newsletter for $275.00 a year. __________________________________________________________________________ >From Phillip G. Ryan Public Relations Release arguing that AI provides a career opportunity for MIS Managers. Provides a rating form for a person's company to see how it stands competitively in applying AI to their needs. This was publicity for Software People Concepts Inc. and AI Services Company. Also another one publicizing the same two companies saying that 40 percent of the largest 500 companies are actively pursuing AI but that it's not MIS people doing the work. They are also publicizing Halbrecht Associates arguing that demand for expert systems developers is high but that there is practically no demand for "natural language, speech input/output, vision systems, automatic theorem proving, automatic programming and super computing" Companies are turning to traditional software engineers to do their expert systems. ------------------------------ Date: Mon, 17 Nov 86 10:53 EST From: TAKEFUJI%scarolina.csnet@RELAY.CS.NET Subject: Invitation to USC AI & VLSI Demo From: Dr. Yoshiyasu Takefuji Date: Dec. 6, 1986 Time: 1 PM Place: On the third floor at Engineering Building in Columbia, South Carolina Hello. We will have project presentation/demonstration on the following subjects: 19 graduate students and 17 undergraduate students are involved in these projects. 1. Fuzzy inference VLSI parallel-engine 2. Fuzzy rule translator and simulator 3. Expert system for determination of fuzzy inference engine architecture 4. Paramodulation VLSI inference engine(pattern matcher) 5. Function Description Translator from behavior description to VLSI layout level (CIF or Magic file) 6. Terminal-based local network project to eliminate RS232c wire-jungle 7. Case studies of knowledge acquisition 8. Graphic Applications Let me know whether you can come to see our demo. csnet: takefuji%scarolina.edu usenet: ncrcae!usccmi!takefuji Thank you. ------------------------------ Date: 18 Nov 1986 10:27 EST (Tue) From: Claudia Smith Subject: Seminar - Trajectory Planning in Time-Varying Environments (MIT) TRAJECTORY PLANNING IN TIME VARYING ENVIRONMENTS Kamal Kant Gupta McGill University Montreal,Canada ABSTRACT: We present a novel approach to solving the trajectory planning problem (TPP) in time-varying environments. The essence of our approach lies in a heuristic but natural decomposition of TPP into two subproblems: (1) planning a path to avoid collision with static obstacles and (2) planning the velocity along the path to avoid collision with moving obstacles. We call the first subproblem the path planning problem (PPP) and the second the velocity planning problem (VPP). Thus, our decomposition is summarized by the equation TPP \rightarrow PPP + VPP. The symbol \rightarrow indicates that the decomposition holds under certain assumptions, e.g., when obstacles are moving independently of (i.e. not tracking) the robot. Furthermore, we pose the VPP in path-time space, where time is explicitly represented as an extra dimension, and reduce it to a graph search in this space. In fact, VPP is transformed to a two-dimensional PPP in path-time space with some additional constraints. Algorithms are then presented to solve the VPP with different optimality criteria: minimum length in path-time space, and minimum time. DATE: Tuesday, Nov. 18th TIME: 3pm PLACE: NE43-773 (7th floor conference room) HOST: Prof. Brooks ------------------------------ Date: 18 Nov 86 22:28:22 EST From: Steven.Minton@k.cs.cmu.edu Subject: Seminar - An Expert System for Building Layout (CMU) This week's seminar is being given by Robert Coyne and Tim Glavin. As usual, Friday, 3:15 in 7220. ABSTRACT: We report on work in progress on a generative expert system for the design of building layouts that can be adapted to various problem domains. The system does not reproduce the behavior of human designers; rather, it intends to complement their performance through (a) its ability to systematically search for alternative solutions with promising trade-offs; and (b) its ability to take a broad range of design concerns into account. Work on the system also aims at providing insights into the applicability of artificial intelligence techniques to space planning and building design in general. Spacial relations between the objects to be allocated serve as basic design variables which define differences between layouts. They are represented by a novel scheme, called an orthogonal structure, which allows us to enumerate layouts in an abstract space, following a 'least commitment' strategy with regard to details such as the dimensions of the objects. The representation, and the generator based on it, are general and flexible enough to allow generation of layouts in various 'domains'. The knowledge required to distinguish good or 'best' layouts in particular domains is located in special testers which are to be built up through the process of 'knowledge acquisition' as it typically occurs in the development of expert systems. ------------------------------ Date: Wed, 19 Nov 86 22:31:02 EST From: "Steven A. Swernofsky" Subject: Seminar - New Paths in Knowledge Engineering (BBN) The Science Development Program will present professor Donald Michie of the Turing Institute of Scotland as the next speaker in the Guest Lecture series. His lecture will take place on Thursday, November 20 at 4:30 p.m. in the Newman Auditorium, Bolt Beranek and Newman Inc., 70 Fawcett Street, Cambridge, Ma. Dr. Michie will be lecturing on the topic "New Paths in Knowledge Engineering." Following is an abstract of his talk: Artificial Intelligence is not something sudden. It has been on the road for centuries. In intellectual terms the task is to complement the mathematical universalism of physics with a logic praticular to man. New approaches based on this shift of philosophy are today breaking into the market place, driven by certain pressing industrial and military requirements. ------------------------------ End of AIList Digest ******************** From LAWS@KL.SRI.COM Tue Dec 15 02:24:29 1987 Mail-From: LAWS created at 24-Nov-86 00:32:22 Date: Mon 24 Nov 1986 00:30-PST From: AIList Moderator Kenneth Laws Reply-To: AIList@SRI-STRIPE.ARPA Us-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025 Phone: (415) 859-6467 Subject: AIList Digest V4 #265 To: AIList@SRI-STRIPE.ARPA Resent-Date: Mon 14 Dec 87 22:42:37-PST Resent-From: Ken Laws Resent-To: isr@vtopus.CS.VT.EDU Resent-Message-Id: <12358590030.16.LAWS@KL.SRI.COM> Status: R AIList Digest Monday, 24 Nov 1986 Volume 4 : Issue 265 Today's Topics: Queries - GLISP & PEARL & PD OPS5 and/or LISP, AI Tools - KEE on Symbolics vs. Xerox, Education - Cognitive Science Programs, Ethics - AI and the Arms Race ---------------------------------------------------------------------- Date: Thu, 20 Nov 86 14:03:05 est From: rochester!tropix!dls@seismo.CSS.GOV (David L. Snyder ) Reply-to: tropix!dls@seismo.CSS.GOV (David L. Snyder ) Subject: glisp info request Someone asked me about glisp today, and all I could remember/say is that I thought Gordon Novak had written it. Anyone out there care to refresh my memory/enlighten me? Thanks. David Snyder GCA/Tropel Division 60 O'Connor Road Fairport, NY 14450 P.S. Try tropix!dls@rochester as an arpa address if other alternatives fail. ------------------------------ Date: 20 Nov 86 18:53:56 GMT From: ritcv!tropix!dls@ROCHESTER.ARPA (David L. Snyder ) Subject: PEARL info request A few questions about pearl (Package for Efficient Access to Representations in Lisp): Can anyone tell me what, if any, activity is going on with pearl these days? (Is the pearl-bugs mailing list still active?) Has anyone used it for non-toy problems? Any chance it'll be ported into common lisp? Is there something better that superceeds it (and is in the public domain)? Thanks! P.S. Try tropix!dls@rochester as an arpa address if other alternatives fail. ------------------------------ Date: 21 Nov 86 20:01:08 GMT From: decvax!wanginst!sullivan@ucbvax.Berkeley.EDU (Brian Sullivan) Subject: PD OPS5 and/or LISP ??? Sorry if this question has already been asked. I am a new subscriber to this news group. Does anyone know of a public domaim or low-cost ops5 for the IBM or Wang PC? Does anyone know of a public domaim or low-cost lisp for the IBM or Wang PC? Please reply to the address below, thanks in advance. ------- Brian M. Sullivan sullivan@wanginst (Csnet) Wang Institute of Graduate Studies decvax!wanginst!sullivan (UUCP) Tyng Road, Tyngsboro, MA 01879 (617) 649-9731 ------------------------------ Date: 19 Nov 86 08:49 EST From: SHAFFER%SCOVCB.decnet@ge-crd.arpa Subject: KEE on Symbolics vs. Xerox We are working on projects using Intellicorp's KEE on a Symbolics system. We had been running KEE 2.1 using Zetalisp 6.1,2,3. Recently, we have received the updates for both products. The new KEE 3.0 incorporates the "worlds" concept along with an implementation of Asumption-based Truth Maintenance System. (ABTMS) The lastest version of Zetalisp is Symbolics Common Lisp. (Genera 7.0) Is anyone else out there is a similar environment? We are interested in the following situations: 1) KEE 2.1 to 3.0 conversion problems a) using "worlds" b) using ABTMS c) using KEEPictures 2) Genera 7.0 performance a) FLAVORS b) presentation types 3) KEE environments a) KEE 2.1 on Zetalisp b) KEE 3.0 on Zetalisp c) KEE 2.1 on Genera 7.0 d) KEE 3.0 on Genera 7.0 I would like to comment on the Symbolics Vs Xerox debate. It seems to me that the discussion should involve a real life application that runs on both machines. For example, KEE or ART. And since Xerox and Symbolics will both be using Common Lisp, even the language will be similar. Create a portable, interactive application using KEE, lets say, and run it on both machines similarly equiped. Wouldnt this be a better thing than long, long, stories about someone's dated experiences on one of the two machines. ------------------------------ Date: 21 Nov 86 22:19:34 GMT From: milano!conklin@im4u.utexas.edu Subject: Re: choosing grad schools When I was there three years ago U. Mass. (Amherst) had an aggressively interdisciplinary approach to Cognitive Science, involving the Computer Science (COINS), Linguistics, Psychology, and Philosophy departments. While there was no single department and no degree, there was active encouragement for students to take courses in the other departements, and many advanced seminars were co-lead by faculty of several departments. I don't know the status of things now, especially since Michael Arbib, a chief architect of that approach, has gone on to USC in LA. -- Jeff Conklin MCC Software Technology Program (512) 338-3562 conklin@MCC.arpa ut-sally!im4u!milano!conklin ------------------------------ Date: Fri, 21 Nov 86 10:54:04 EST From: "William J. Rapaport" Subject: Cognitive Science at SUNY Buffalo GRADUATE GROUP IN COGNITIVE SCIENCE STATE UNIVERSITY OF NEW YORK AT BUFFALO Buffalo, NY 14260 Gail A. Bruder William J. Rapaport Department of Psychology Department of Computer Science rapaport@buffalo.csnet Co-Directors, 1986-1987 Cognitive Science is an interdisciplinary effort intended to investigate the nature of the human mind. This effort requires the theoretical approaches offered by computer science, linguistics, mathematics, philo- sophy, psychology, and a host of other fields related by a mutual interest in intelligent behavior. The Graduate Group in Cognitive Science was formed to facilitate cognitive science research at SUNY Buffalo. Its activities have focused upon language-related issues and knowledge representation. These two areas are important to the development of cognitive science and are well represented at SUNY Buffalo by the research interests of faculty and graduate students in the group. Since its formal recognition in April 1981, the Graduate Group has grown quickly. Currently, its membership of over 150 faculty and gradu- ate students is drawn from the Departments of Computer Science; Psychol- ogy; Linguistics; Communicative Disorders and Sciences; Philosophy; Instruction; Communication; Counseling and Educational Psychology; Edu- cational Organization, Administration, and Policy Studies; the Intensive English Language Institute; Geography; and Industrial Engineering; as well as other area colleges and universities. The Group sponsors lec- tures and informal discussions with visiting scholars; discussion groups focused on Group members' current research; an interdisciplinary, team- taught, graduate course, "Introduction to Cognitive Science"; a graduate seminar on current topics and issues in language understanding; and a Cognitive Science Library. 1985 COLLOQUIA Our colloquium speakers during 1985 included Andrew Ortony (Psychology, Illinois), David Waltz (Computer Science, Brandeis), Alice ter Meulen (Linguistics, Washington), Joan Bybee (Linguistics, SUNY Buffalo), Livia Polanyi (AI, BBN), Joan Bresnan (Linguistics, Stanford), Leonard Talmy (Linguistics, Berkeley), Judith Johnston (Communicative Disorders, Indi- ana), Richard Weist (Psychology, SUNY Fredonia), and Benjamin Kuipers (AI, Texas). RESEARCH PROJECT A research subgroup of the Graduate Group in Cognitive Science is actively engaged in an interdisciplinary research project investigating narrative comprehension, specifically the role of a "deictic center". Grant proposals, conference papers, publications, and several disserta- tion proposals have come from this collaborative effort. A technical report describing this project--Bruder et al., "Deictic Centers in Nar- rative: An Interdisciplinary Cognitive-Science Project," SUNY Buffalo Department of Computer Science Technical Report No. 86-20--is available from William J. Rapaport, at the above address. Specifically, we are developing a model of a cognitive agent's comprehension of narrative text. Our model will be tested on a computer system that will represent the agent's beliefs about the objects, rela- tions, and events in narrative as a function of the form and content of the successive sentences encountered. In particular, we are concentrat- ing on the role of spatial, temporal, and focal-character information for the cognitive agent's comprehension. We propose to test the hypothesis that the construction and modifi- cation of a deictic center is of crucial importance for much comprehen- sion of narrative. We see the deictic center as the locus in conceptual space-time of the objects and events depicted or described by the sen- tences currently being perceived. At any point in the narrative, the cognitive agent's attention is focused on particular characters (and other objects) standing in particular spatial and temporal relations to each other. Moreover, the agent "looks" at the narrative from the per- spective of a particular character, spatial location, or temporal loca- tion. Thus, the deictic center consists of a WHERE-point, a WHEN-point, and a WHO-point. In addition, reference to characters' beliefs, per- sonalities, etc., are also constrained by the deictic center. We plan to develop a computer system that will "read" a narrative and answer questions about the deictic information in the text. To achieve this goal, we intend to carry out a group of projects that will allow us to discover the linguistic devices in narrative texts, test their psychological reality for normal and abnormal comprehenders, and analyze psychological mechanisms that underlie them. Once we have the results of the individual projects, we will integrate them and work to build a unified theory and representational system that incorporates the significant findings. Finally, we will test the system for coherence and accuracy in modeling a human reader, and modify it as necessary. COURSEWORK The Graduate Group in Cognitive Science provides students with the opportunity for training and research in Cognitive Science at the Ph.D. level. Students must be residents in a host department (Communicative Disorders and Sciences, Computer Science, Linguistics, Philosophy, Psychology), whose requirements must be fulfilled (but which can include coursework in the other Cognitive Science disciplines), and must meet certain additional requirements: enrollment in the graduate course, Introduction to Cognitive Science; and the completion of a "Focus" in one other participating department. Further details are available from the Co-Directors of the Group. The Graduate Group faculty also encourages outstanding undergradu- ates to develop an interest in Cognitive Science. Qualified undergradu- ates may request admission to the graduate course (Introduction to Cog- nitive Science) and can design a major in Cognitive Science under the Special Majors program at SUNY Buffalo. ------------------------------ Date: Fri, 21 Nov 86 10:54:04 EST From: "William J. Rapaport" Subject: Graduate Group in Vision at SUNY Buffalo GRADUATE GROUP IN VISION STATE UNIVERSITY OF NEW YORK AT BUFFALO Buffalo, NY 14260 Malcolm Slaughter Department of Biophysics Director, 1986-1987 It is becoming increasingly important for vision researchers in diverse fields to interact, and the SUNY Buffalo Graduate Group in Vision has been formed to facilitate that interaction. Current membership includes 25 faculty and 25 students from 10 departments (Computer Science, Electrical and Computer Engineering, Industrial Engineering, Geography, Psychology, Biophysics, Physiology, Biochemistry, Philosophy, and Media Studies). The Group organizes a colloquium series and provides central- ized information about activities both on campus and in the local area that are of interest to vision researchers. The Vision Group received formal recognition and funding in April 1986. The 1986-87 activities include: biweekly meetings to discuss the current research being performed in one of the 20 vision laboratories represented in the group; an upper division undergraduate/lower-level- graduate course, which serves as an introduction to interdisciplinary research in vision; and a colloquium series. This year's speakers include Jerry Feldman (Computer Science, Rochester), Peter Shiller (Psychology, MIT), Bela Julesz (Psychology, Bell Labs/Murray Hill), Tomaso Poggio (AI, MIT; tentative), and Ed Pugh (Biophysics, Pennsyl- vania; tentative). ------------------------------ Date: 21 Nov 86 04:32:47 GMT From: rutgers!cbmvax!bpa!burdvax!blenko@SPAM.ISTC.SRI.COM (Tom Blenko) Subject: Re: AI and the Arms Race In article <8611181719.AA00510@watdcsu.uucp> "B. Lindsay Patten" writes: [... stuff ...] |The real point Dr. Weizenbaum was trying to make (in my |opinion) was that we should weigh the good and bad applications of |our work and decide which outweighs the other. If Weizenbaum or anyone else thinks he or she can succeeded in weighing possible good and bad applications, I think he is mistaken. Wildly mistaken. Why does Weizenbaum think technologists are, even within the bounds of conventional wisdom, competent to make such judgements in the first place? Everywhere I turn there is a technologist telling me why SDI cannot succeed -- which tells me that technologists fail to comprehend consequences of their work from any perspective except their own. Is it not possible that the principal consequences of SDI will be something other than an operational defense system? Why doesn't Weizenbaum do some research and talk about it? Why is Waterloo inviting him to talk on anything other than his research results? No reply necessary, but doesn't the fact that technically- oriented audiences are willing to spend their time listening to this sort of amateur preaching itself suggest what their limitations are with regard to difficult ethical questions? Tom ------------------------------ Date: 22 Nov 86 07:46:41 GMT From: anderson@unix.macc.wisc.edu (Jess Anderson) Subject: Re: AI and the Arms Race In article <2862@burdvax.UUCP>, blenko@burdvax.UUCP (Tom Blenko) writes: | Why doesn't Weizenbaum do some research and talk about it? Why is | Waterloo inviting him to talk on anything other than his research | results? No reply necessary, but doesn't the fact that technically- | oriented audiences are willing to spend their time listening to this | sort of amateur preaching itself suggest what their limitations are | with regard to difficult ethical questions? Even as a preacher, Weizenbaum is hardly an amateur! Do be fair. On your last point, I would claim the evidence shows just the opposite of what you claim, namely that technically-oriented audiences are willing to spend their time listening to intelligent opinions shows that they are more qualified than some people think to consider difficult ethical questions. Of course I am an amateur, too -- of life (remember what the word means!). -- ==ARPA:====================anderson@unix.macc.wisc.edu===Jess Anderson====== | UUCP: {harvard,seismo,topaz, 1210 W. Dayton | | akgua,allegra,ihnp4,usbvax}!uwvax!uwmacc!anderson Madison, WI 53706 | ==BITNET:============================anderson@wiscmacc===608/263-6988======= ------------------------------ End of AIList Digest ******************** From LAWS@KL.SRI.COM Tue Dec 15 02:28:55 1987 Mail-From: LAWS created at 24-Nov-86 01:00:05 Date: Mon 24 Nov 1986 00:57-PST From: AIList Moderator Kenneth Laws Reply-To: AIList@SRI-STRIPE.ARPA Us-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025 Phone: (415) 859-6467 Subject: AIList Digest V4 #266 To: AIList@SRI-STRIPE.ARPA Resent-Date: Mon 14 Dec 87 22:42:39-PST Resent-From: Ken Laws Resent-To: isr@vtopus.CS.VT.EDU Resent-Message-Id: <12358590037.16.LAWS@KL.SRI.COM> Status: R AIList Digest Monday, 24 Nov 1986 Volume 4 : Issue 266 Today's Topics: Discussion Lists - Neural Networks Digest & Psychnet, Call for Papers - Journal of Logic Programming, Conferences - Workshop on AI in Process Engineering & IEEE Conference on AI Applications: Advance Program ---------------------------------------------------------------------- Date: Thu, 20 Nov 86 10:41:08 cst From: Mike Gately 995-3273 M/S 154 Subject: Neural Networks Digest ---- NEW DIGEST ANNOUNCEMENT ---- I am starting up a new e-mail Digest which will cover the topic of Neural Networks (both real and imagined). The name of this new mailing list is ---- NEURON ---- You have probably noticed that there has been an increase in the amount of message traffic regarding connectionism on this and other digests. The intent is that this digest will be a focal point for this information. NEURON is open to discussion of any topic related to neurons. This should include: Neural Networks Algorithms Software Simulations Digital Hardware Analog Hardware Optical Hardware Biology Neurophysiology Neuroscience Cellular Automata As you can see, I am attempting to get some interest from the 'wet ware' folks. This may be a first; but the results will surely be interesting. The official starting date of the mailing list is the first of December. I am using the US MAIL to inform many of the researchers in this field that I already know about. If you are interested in receiving this Digest, reply to CSNET: NEURON@TI-CSL ARPANET: NEURON%TI-CSL.CSNET%RELAY.CS.NET@CSNET-RELAY.ARPA with your current net address. If you expect that a large number of folks from you site will want to receive this digest, contact your site postmaster to set up a redistribution file and have him/her send me a single site address. As I receive addresses from you, I will try to send out a Welcome message. If you do not receive this within 4 work days please resend your request information (I hope this isn't a mistake). If you responded to Mitch Wyle's message of 2 weeks ago about such a Digest, he has forwarded those messages to me. Regards, Michael T. Gately Texas Instruments, Inc. Advanced Concepts Branch GATELY%CRL1%TI-CSL.CSNET%RELAY.CS.NET@CSNET-RELAY.ARPA ------------------------------ Date: Sat, 22 Nov 86 13:28:39 CST From: Psychnet Newsletter and Bulletin Board Reply-to: EPSYNET%UHUPVM1.BITNET@WISCVM.WISC.EDU Subject: announcement for AIlist Persons interested in artificial intelligence who also have interests in psychology may wish to subscribe to the Psychnet Newsletter via the net. Contributors from time to time even include such persons as the (in)famous Stevan Harnad! To subscribe send your request to: epsynet%uhupvm1.bitnet@wiscvm.wisc.edu Thanks, Bob Morecock, Psychnet Editor ------------------------------ Date: Wed, 12 Nov 86 22:01:45 EST From: Leon Sterling Reply-to: Leon Sterling Subject: Call for papers -Journal of Logic Programming Call for Papers Papers are requested for a special issue of the Journal of Logic Programming concerned with Applications of Logic Programming for Knowledge-Based Systems The papers should describe applications which exploit special features of logic programming. Two examples: a problem solved by using a logic programming language where the solution would be more difficult to state in another language; or the development of a methodology for the more effective use of logic programs. The reported research should be original and should not have appeared elsewhere. Updates of successful, ongoing projects containing material not otherwise available will also be considered. Applications of interest include, but are not limited to: Financial expert systems Diagnosis systems Medical expert systems Configuration systems Expert system tools VLSI design Natural language programs Problem-solving Programming environments Learning Please send 4 copies of your paper by May 31, 1987 to Leon Sterling, Department of Computer Engineering and Science, Case Western Reserve University, Cleveland, Ohio, USA 44106 Electronic mail address: CSNET: leon@case UUCP: ...!decvax!cwruecmp!leon ------------------------------ Date: Thu 20 Nov 86 16:26:38-EST From: V. Venkatasubramanian Subject: Workshop on AI in Process Engineering... WORKSHOP ON ARTIFICIAL INTELLIGENCE IN PROCESS ENGINEERING Place: COLUMBIA UNIVERSITY, Kellogg Auditorium Date: March 9-10, 1987 Deadline: Dec 22, 1986 for the submission of applications for attending the workshop. Sponsored by: American Association for Artificial Intelligence Air Products Amoco 1. Themes and Motivations: In the past few years there has been considerable work in applying recent advances in Artificial Intelligence to problems in the various disciplines of engineering. Substantial impact has already been seen in electrical, mechanical, and civil engineering applications. It is now well-recognized that the domain of Process Engineering also has much to gain from applications of AI. Particular attention is being paid to fault diagnosis and control, process design and planning. Interest in the process engineering community (both in academia and in industry) is substantial, but only a handful of researchers are currently engaged in applying AI to problems in process engineering. This is largely due to lack of proper exposure of this novel area to the rest of the community. This workshop is being organized to provide this much needed exposure to researchers in academia and industry. Thus the workshop will serve the following current needs: - Bring together for an intense program, people in academia as well as in industry who are interested in AI in process engineering. - Disseminate the ideas and techniques of AI in an appropriate form by relating them to fault diagnosis and control, design and planning applications in process engineering. - Provide demonstrations of some expert system prototypes in process engineering. - Help resolve the confusion about what AI can do, how to go about applying AI for process engineering problems, etc. - To provide a long-term research focus, identify a set of problems that have important basic research issues, as well as useful practical components. 2. Workshop Subjects: * Fault Diagnosis * Design * Operations 3. Workshop Speakers: Chemical Engineering: Prof. Jim Davis (Ohio State), Prof. Prasad Dhurjati (Delaware) Prof. George Stephanopoulos (MIT), Prof. V. Venkatasubramanian (Columbia) Prof. Art Westerberg (Carnegie-Mellon) Computer Science: Prof. B. Chandrasekaran (Ohio State), Prof. Ken Forbus (Univ. of Illinois) Dr. Jeff Pan (Schlumberger Research), Dr. John Kunz (Intellicorp) 4. Workshop Participation: For the workshop to be intense, stimulating, and useful, we feel that the number of partcipants must be limited. Hence the number of participants, besides the invited speakers, will be limited to fifty. Interested parties are urged to contact one of the members of the organizing committee (given below) before Dec 22nd by writing a letter describing their background, research interests, and current process engineering problems they are working on. The organizing committee will select the participants from the applicant pool. Participation is by invitation only. The registration fee is $ 150 for the two-day workshop and will include a copy of the proceedings. 5. Organizing Committee: Prof. V. Venkatasubramanian, Chairman Intelligent Process Engineering Laboratory Department of Chemical Engineering Columbia University New York, NY 10027. (212) 280-4453 Prof. G. Stephanopoulos, Co-Chairman Laboratory for Intelligent Systems in Process Engineering Department of Chemical Engineering Massachusetts Institute of Technology Cambridge, MA 02139. (617) 253-3904 Prof. James Davis Department of Chemical Engineering Ohio State University Columbus, OH 43210. (614) 292-0090 ------------------------------ Date: Thu 20 Nov 86 17:28:23-CST From: Jim Miller Subject: IEEE Conference on AI Applications: Advance Program THE THIRD IEEE CONFERENCE ON ARTIFICIAL INTELLIGENCE APPLICATIONS Advance Program Orlando Hyatt Regency Orlando, Florida February 23-28, 1987 Sponsored by the Computer Society of the IEEE For information on any part of the conference, please contact: The Third IEEE Conference on AI Applications Computer Society of the IEEE 1730 Massachusetts Avenue NW Washington DC 20036-1903 202-371-1013 Conference Committee: General Chair: Program Chairs: Jan Aikins James Miller Aion Corporation Elaine Rich MCC Tutorials Chair: For the Computer Society Paul Harmon of the IEEE: Harmon Associates William Habingreither Program Committee: William J. Clancey Keith Clark Stanford University Imperial College Byron Davies Michael Fehling Texas Instruments Rockwell International Mark Fox Bruce Hamill Carnegie-Mellon University Applied Physics Laboratory and Carnegie Group Inc Johns Hopkins University Peter Hart Elaine Kant Syntelligence Schlumberger-Doll Research Paul Kline Benjamin Kupiers Texas Instruments University of Texas John McDermott Roy Maxion Carnegie Mellon University Carnegie Mellon University Charles Petrie Bruce Porter MCC University of Texas John Roach Marty Tenenbaum Virginia Tech Schlumberger Harry Tennant Michael D. Williams Texas Instruments IntelliCorp ============================================================================== Wednesday, February 25, 1987 ============================================================================== 9:00 - 10:00: KEYNOTE ADDRESS AI and Natural Language in the Real World Gary Hendrix, Symantec 10:00 - 10:30: BREAK 10:30 - 12:00: INVITED TALKS: Viewing Knowledge Bases as Qualitative Models William J. Clancey, Stanford University Second-Generation Manufacturing Systems Mark Fox, Carnegie Mellon University and Carnegie Group Inc 10:30 - 12:00: Paper Session 1A: KNOWLEDGE ACQUISITION Verifying Consistency of Production Systems T. A. Nguyen, Lockheed Principles of Design for Knowledge Acquisition Thomas Gruber, University of Massachusetts Probabilistic Inference Won D. Lee, University of Texas at Arlington; Sylvian R. Ray, University of Illinois 10:30 - 12:00: Paper Session 1B: QUESTION ANSWERING Question Answering with Rhetorical Relations Wanying Jin and Robert F. Simmons, University of Texas at Austin Question-Driven Approach to the Construction of Knowledge-Based Software Advisor Systems Patrick Constant, Stainslaw Matwin and Stainslaw Szpakowicz, University of Ottawa 12:00 - 1:30: LUNCH 1:30 - 3:30: Paper Session 2A: MANUFACTURING A Knowledge-based Approach to Printing Press Configuration M. S. Lan, R. M. Panos, and M. S. Balban, Rockwell International A Knowledge Based Imaging System for Electromagnetic Nondestructive Testing L. Udpa and W. Lord, Colorado State University An Object-Based Architecture for Manufactured Parts Routing R. L. Young, D. M. O'Neill, P. W. Mullarkey, P. C. Gingrich, A. Jain, and S. Sardana, Schlumberger-Doll Research Expert System for Visual Solder Joint Inspection Sandra L. Bartlett, Charles L. Cole, amd Ramesh Jain, University of Michigan 1:30 - 3:30: Paper Session 2B: KNOWLEDGE REPRESENTATION Breaking the Primitive Concept Barrier Robert Kass, Ron Katriel, and Tim Finin, University of Pennsylvania FRAMEWORKS: A Uniform Approach to Knowledge Representation for Natural Language Processing Howard R. Smith, Warren H. Harris, and Dan Simmons, United Technologies Modeling Connections for Circuit Diagnosis Mingruey R. Taie and Sargur N. Srihari, State University of New York at Buffalo CONGRES: Conceptual Graph Reasoning System Anand S. Rao and Norman Y. Foo, University of Sydney 1:30 - 3:30: INVITED PANEL The Challenges of Integrating AI into Real-Time Control and C^2 Moderator: J. R. Gersh, Johns Hopkins University Applied Physics Laboratory 3:30 - 4:00: BREAK 4:00 - 5:30: PLENARY PANEL Programming Languages for AI: Lisp vs. Conventional Languages Moderator: Mark Miller, Computer * Thought Corporation ============================================================================== Thursday, February 26, 1987 ============================================================================== 9:00 - 10:00: KEYNOTE ADDRESS Expert Systems in a General Cognitive Architecture John Laird, University of Michigan 10:00 - 10:30: BREAK 10:30 - 12:00: Paper Session 3A: EXPLANATION-BASED LEARNING Analyzing Variable Cancellations to Generalize Symbolic Mathematical Calculations Jude W. Shavlik and Gerald F. DeJong, University of Illinois Extending Explanation-Based Learning: Failure-Driven Schema Refinement Steve A. Chien, University of Illinois A Learning Apprentice System for Mechanical Assembly Alberto Maria Segre, University of Illinois 10:30 - 12:00: Paper Session 3B: AI AND REAL-TIME PROGRAMMING Real Time Process Management for Materials Composition in Chemical Manufacturing Bruce D'Ambrosio and Peter Raulefs, FMC Corporation, Michael R. Fehling and Stephanie Forrest, Teknowledge Knowledge-Based Experiment Builder for Magnetic Resonance Imaging (MRI) Systems J. Sztipanovits, C. Biegl, G. Karsai, J. Bourne, C. Harrison, and R. Mushlin, Vanderbilt University YES/L1: Integrating Rule-Based, Procedural, and Real-time Programming for Industrial Applications A. Cruise, R. Ennis, A. Finkel, J. Hellerstein, D. Loeb, M. Masullo, K. Milliken, H. Van Woerkom, N. Waite, IBM; D. Klein, University of Pennsylvania 10:30 - 12:00: INVITED PANEL Delivery in the Real World Moderator: Esther Dyson, EDventures Holding, Inc. 12:00 - 1:30: LUNCH 1:30 - 3:30: Paper Session 4A: DIAGNOSIS LVA: A Knowledge-based System for Diagnosing Faults in Digital Data Loggers S. C. Laufmann and R. S. Crowder III, Batelle Pacific Northwest Laboratory A Multiparadigm Knowledge-based System for Diagnosis of Large Mainframe Peripherals David W. Rolston, Honeywell Distributed Diagnosis of Systems with Multiple Faults Hector Geffner and Judea Pearl, UCLA Testing, Verifying, and Releasing an Expert System: The Case History of Mentor Edward L. Cochran and Barbara L. Hutchins, Honeywell 1:30 - 3:30: Paper Session 4B: ROBOTICS AND PERCEPTION On the Terrain Acquisition by a Point Robot Amidst of Polyhedral Obstacles Nageswara S. V. Rao, S. S. Iyengar, Louisiana State University; B. John Oommen, Carelton University; R. L. Kashyap, Purdue University A Computational Theory and Algorithm for Fluent Reading Jonathan J. Hull, State University of New York at Buffalo Automated Reasoning about Machine Geometry and Kinematics Andrew Gelsey, Yale University Color Separation Using General-Purpose Computer Vision Algorithms Deborah Walters, University of Buffalo 1:30 - 3:30: Paper Session 4C: CASE STUDIES FRESH: A Naval Scheduling System Michael Babin, Michael Gately, and Michael Sullivan, Texas Instruments Building Near-Term Fieldable Militry AI Systems: Formalisms and an Example Mark L. Akey and Kirk A. Dunkelberger, Magnavox Rule-Based Flexible Control of Tutoring Process in Scene-oriented CAI systems Ichiro Morihara, Toru Ishida, and Hiroyuki Furuya, NTT Electrical Communications Laboratory Abductive and Deductive Inference in an Expert System Jacqueline A. Haynes and Joshua Lubell, University of Maryland 3:30 - 4:00: BREAK 4:00 - 5:30: PLENARY PANEL The Future of AI Applications: An Industry Perspective Panelists: Walden C. Rhines; Texas Instruments, Herbert Schorr, IBM; Thomas P. Kehler, IntelliCorp Moderator: Esther Dyson, EDventures Holding, Inc. ============================================================================== Friday, Feburary 27, 1986 ============================================================================== 9:00 - 10:00: KEYNOTE ADDRESS Overcoming the Brittleness Bottleneck: Douglas B. Lenat, MCC 10:00 - 10:30: BREAK 10:30 - 12:00: Paper Session 5A: SEARCH The Cycle-Cutset Method for Improving Search Performance in AI Applications Rina Dechter and Judea Pearl. UCLA Schedule Optimization with Probabilistic Search Lawrence Davis and Frank Ritter, Bolt Beranek and Newman 10:30 - 12:00: Paper Session 5B: UNCERTAINTY Uncertain Inference Using Belief Functions Sunggu Lee and Kang G. Shin, University of Michigan Truth Maintenance with Numeric Certainty Estimates Bruce D'Ambrosio, FMC Corporation A Real-Time AI System for Military Communications M. E. Ulug, General Electric 10:30 - 12:00: INVITED TALKS Judging the Risk: Expert Systems in Finance Peter Hart, Syntelligence Artificial Intelligence: Expectations vs. Reality Jay M. Tenenbaum, Schlumberger Palo Alto Research 12:00 - 1:30: LUNCH 1:30 - 3:30: Paper Session 6A: DEFAULT REASONING A Framework for Describing Troubleshooting Behavior Using Default Reasoning and Functional Abstraction Michael Young, Stanford University Assumption Based Reasoning Applied to Personal Flight Planning Adithya M. Rao and Gautam Biswas, University of South Carolina; Prasanta K. Bose, Texas Instruments Classification by Semantic Matching Paul R. Cohen, Philip M. Stanhope, and Rick Kjeldsen, University of Massachusetts Default Reasoning -- Extension and Semantics Keki B. Irani and Zhaogang Qian, University of Michigan 1:30 - 3:30: Paper Session 6B: DESIGN AND PLANNING Goal Directed Planning of the Design Process Christopher Tong, Rutgers University Concerns: A Means of Identifying Potential Plan Failures Marc Luria, University of California at Berkeley A VLSI Design Automation System Using Frames and Logic Programming Takayoshi Yokota, Keisuke Bekki, and Nobuhiro Hamada, Hitachi Research Laboratory PLEX: A Knowledge Based Placement Program for Printed Wire Boards Sankar Virdhagriswaran, Sam Levine, Scott Fast, and Susan Pitts, Honeywell 1:30 - 3:30: Paper Session 6C: SOFTWARE AND TOOLS Engineous: A Knowledge Directed Computer Aided Design Shell Dennis J. Nicklaus, Siu S. Tong, and Carol J. Russo, General Electric Implementing Distributed AI Systems Les Gasser, Carl Braganza, and Nava Herman, USC AI Based Software Maintenance Lori B. Alperin and Beverly I. Kedzierski, Carnegie Group Inc Application of Correlation Measures for Validating Structured Selectors Keith A. Butler, Boeing ============================================================================== Tutorial Program ============================================================================== Monday, February 12, 1987 Morning: Managing Knowledge System Development Avron Barr, Aldo Ventures Programming in the Lisp Machine Environment Sue Green, Texas Instruments Afternoon: Analyzing Expert System Building Tools Paul Harmon, Harmon Associates Logic Programming, Expert Systems, and Databases Steve Hardy, Teknowledge Tuesday, February 13, 1987 Morning: AI and Computer Integrated Manufacturing Arvind Sathi, Carnegie Group Inc Commercial Applications of Natural Language Processing Tim Johnson, Ovum Ltd. Afternoon: AI Programming on Parallel Machines Joe Brandenburg, Intel Intelligent Interfaces Marilyn Stelzner, IntelliCorp ------------------------------ End of AIList Digest ********************