LAWS@SRI-AI.ARPA (05/17/85)
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-AI> AIList Digest Thursday, 16 May 1985 Volume 3 : Issue 64 Today's Topics: Queries - PROLOG on INTERLISP/LOOPS & Lisp Machines & Microcomputer Lisps & Statecharts, Machine Translation - Update, Expert Systems - Prospector on a PC, Seminars - Diagnosing Multiple Faults (SU) & Fixpoint Extensions of First-Order Logic (CMU) & A New "Turing" Thesis (CMU), Course - Model Theory (CMU) ---------------------------------------------------------------------- Date: 13 May 85 18:06:35 EDT From: Louis Steinberg <STEINBERG@RUTGERS.ARPA> Subject: PROLOG on INTERLISP/LOOPS Can anyone point me to an implementation of PROLOG that will run on a Xerox Lisp machine, i.e. is implemented in Interlisp-D or Interlisp-D with LOOPS? I know of Ken Kahn's version but that unfortunately does not use standard LOOPS. This is for an educational environment so efficiency is not essential. Also welcome would be advice on porting some other, existing version. Lou Steinberg STEINBERG @ RUTGERS ------------------------------ Date: Tue, 14 May 85 15:32:55 pdt From: Curtis L. Goodhart <goodhart%cod@Nosc> Subject: Lisp Machines Anybody have any pointers to some good references for explaining the architectural characteristics of a lisp machine, ie why do you need a specific kind of machine, as opposed to a conventional computer, to run lisp? Thanks, Curt Goodhart (goodhart@nosc ;on the arpanet) ------------------------------ Date: Wed, 15 May 85 10:23 EST From: John N Frampton <frampton%northeastern.csnet@csnet-relay.arpa> Subject: Microcomputer Lisps comparable to GCLISP I am writing a review of GCLISP for a computer magazine. I have used MULISP and IQLISP on an IBM PC previously but just found out yesterday that there are several new Lisp implementations for the IBM PC which are competitive with GCLISP. I would appreciate very much getting a short description of these products to include in the GCLISP review. I would have preferred to do a comparison, but it's too late for that. At least I can say what's out there. I'd like a short description (better shorter and sooner than longer and later) - particularly touching on the extent to which they implement Common Lisp (if they do) and if they have a compiler. Reply directly to me (and the board if you want). Thanks, John Frampton ------------------------------ Date: Monday, 13 May 1985 15:02-EDT From: rh@Mitre-Bedford Subject: STATECHARTS Dave Harel was to have given a talk "Statecharts: A Visual Approach to Complex Systems" last week at MIT. I'd be interested in anyone's impressions who attended or otherwise knows about this work. Are there any available references? Thanks, Rich Hilliard ------------------------------ Date: Tue 14 May 85 11:08:50-MDT From: Pete Tinker <tinker@UTAH-20.ARPA> Subject: Machine Translation Update A friend of mine who works as a consultant for Weidner informs me of some corrections to the information posted by Petitpierre on Machine Translation. Only the address for ALPS was given, but the message could be construed to also be the address of their competitor, Weidner. Weidner is no longer in Provo, Utah, and is no longer called Weidner. The correct name and address are WCC Suite 300 40 Skokie Boulevard Northbrook, Illinois 60062 (312) 564-8122 Also, Siemens has an active MT group in Boca Raton, Florida; LOGOS does MT in Boston (Petitpierre mentioned only their European branches). ISSCO is also in Sorrento Valley, California, but I don't know if they work in MT there. -Pete Tinker ------------------------------ Date: Tue 14 May 85 10:57:37-PDT From: HART@SRI-AI.ARPA Subject: Prospector on a PC Ken, I saw a copy of the "Prospector on a PC" query, and thought your AIList readers might be interested in the following clarifications and update. First, the role of Prospector in the famous molybdenum strike: Unfortunately for journalists, an accurate account of the role played by Prospector is not simply stated, and a simple account is not likely to be accurate. Prompted by the confusion surrounding these events (notwithstanding a research report that appeared in Science in 1982), Dick Duda, Rene' Reboh and I submitted a rather lengthy letter to the AI Journal that lays out the details quite carefully. Since the letter should be appearing shortly, and in recognition of my own admonition about simple statements, I will say here only that the evaluation of the moly prospect was intended purely as a scientific experiment and that Prospector's predictions were confirmed to a high degree by independent means. Second, Prospector's origins and descendants: My first notes on the subject date from early 1974, and were motivated by the early success of MYCIN. The project began in earnest in 1975, with Dick Duda, Nils Nilsson, Georgia Sutherland and a geologist named Alan Campbell as the earliest contributors. Rene Reboh joined the project shortly thereafter, and John Gaschnig a couple of years after that. Since the earliest implementation there have been many other contributors and any number of implementations on other machines. Some of the earliest small-machine systems were done by Rene Reboh (on an Apple II) and by John Reiter on a PDP-11. These and other ports generally are not as powerful as the original PDP-10 version, but have been useful nonetheless. The USGS has done a port to the IBM/PC, and Alan Campbell has done an independent port to the IBM/PC and is marketing his as "The Deciding Factor." Coincidentally, a user's review of The Deciding Factor appeared in last Sunday's (May 12) San Jose Mercury by Ray Levitt, a Civil Engineering professor at Stanford. (He liked it, by the way.) I am told that some mining companies are interested in Campbell's version; however, any discussion of use by commercial companies must begin with the recognition that the North American mining industry has been in a severely depressed state for quite some years. The US Geological Service has an active program underway to extend and use Prospector. They have the PC version mentioned above, as well as a Xerox 1108 version. There are something like 30 - 35 models that have been developed (a "model" is a major module of the knowledge base). The Survey has used Prospector to evaluate mineral potential in Alaska and in New England, and has stated (in writing) that the results obtained were in their view superior to what would have been otherwise achievable. (Incidentally, the USGS has a charter to assess resource potential over large tracts of land rather than "to discover a mine".) The Survey also has some 8-10 models under active development for the PC version, and is planning to use the 1108 version for geographically-organized data. Finally, I am told that their systems and plans have achieved a very high level of visibility and excitement in their parent agency, the Dept. of Interior, although the current size of the effort is not large. Does this discussion answer the question of what a PC expert system can do? Obviously not, but I hope it adds more light than heat to the current discussions. In any case, a lot of the value of an expert system lies in the knowledge base; I agree with Karnicky's observation that, regardless of implementation, it's a long way from choosing red wine to discovering an ore deposit. Cheers, Peter ------------------------------ Date: Tue 14 May 85 12:41:00-PDT From: Carol Wright/Susie Barnes <WRIGHT@SUMEX-AIM.ARPA> Subject: Seminar - Diagnosing Multiple Faults (SU) SIGLUNCH DATE: Friday, May 17, 1985 LOCATION: Braun Audiltorium, Mudd/Chemistry Building TIME: 12:05 SPEAKER: Johan Dekleer Xerox TITLE: Diagnosing Multiple Faults Diagnostic tasks require determining the differences between a model of an artifact and the artifact itself. The differences between the manifested behavior of the artifact and the predicted behavior of the model guide the search for the difference between the artifact and its model. The diagnostic procedure presented in this paper reasons from first principles, inferring the behavior of the composite device from knowledge of the structure and function of the individual components comprising the device. The novel contributions of this research are: Multiple-faults: No presupposition is made about the number of failed components. Measurements: Proposes optimal measurements to localize the fault. Probabilistic: A priori probabilities of component faultedness are taken into account. Intermittency: The approach is robust in response intermittent faults. The system is based on incorporating probabilistic information into an Assumption-Based Truth Maintenance System. ------------------------------ Date: 10 May 1985 1429-EDT From: Lydia Defilippo <DEFILIPPO@CMU-CS-C.ARPA> Subject: Seminar - Fixpoint Extensions of First-Order Logic (CMU) APPLIED LOGIC SEMINAR Speaker: Yuri Gurevich (University of Michigan) Date: Wednesday, May 15 Time: 2:00 - 3:15 Place: 5409 WeH Topic: Fixpoint extensions of first-order logic In 1979 Aho and Ullman noted that the relational calculus is unable to express the transitive closure of a given relation, and suggested extending the relational calculus by adding the least fixed point operator. From the point of view of the expressive power, the relational calculus is exactly first-order logic. Aho and Ullman's paper triggered an extensive study of the expressive power of fixpoint extensions of first-order logic with emphasis on finite structures. We survey the results of this study. ------------------------------ Date: 10 May 1985 1433-EDT From: Lydia Defilippo <DEFILIPPO@CMU-CS-C.ARPA> Subject: Seminar - A New "Turing" Thesis (CMU) JOINT LOGIC COLLOQUIUM Speaker: Yuri Gurevich (University of Michigan) Date: Thursday, May 16 Time: 2:00 - 3:30 Place: 4605 WeH Topic: A new thesis Turing's thesis is that every computable function can be computed by an appropriate Turing machine. The informal proof of the thesis gives more: every computing device can be simulated by an appropriate Turing machine. The following much stronger form of the thesis seems to be very much accepted today: every sequential computing device can be simulated by an appropriate Turing machine in polynomial time. Turing machines are computational devices with unbounded resources. First, we adapt Turing's thesis to the case when only devices with bounded resources are considered. Second, we define a more general kind of abstract computational devices, called dynamic structures, and put forward the following new thesis: Every computational device an be simulated by an appropriate dynamic structure - of approximately the same size - in real time: a uniform family of computational devices can be uniformly simulated by an appropriate family of dynamic structures in real time. In particular, every sequential computational device can be simulated by an appropriate sequential dynamic structure. A contribution of Andrea Blass is acknowledged. Descriptions of computational devices are solicited for further confirmation of the thesis. ------------------------------ Date: 7 May 1985 1140-EDT From: Lydia Defilippo <DEFILIPPO@CMU-CS-C.ARPA> Subject: Course - Model Theory (CMU) [Forwarded from the CMU bboard by Laws@SRI-AI.] Department of Mathematics CARNEGIE-MELLON UNIVERSITY COURSE ANNOUNCEMENT - MODEL THEORY Instructor: Ana Pasztor Textbook: Model Theory, by Chang and Keisler, North Holland, 1973 When: Fall 1985, MWF - 2:30-3:20, Porter Hall 125C Note: If you would like to take this course and have conflicts with the time, PLEASE LET ME KNOW. (Room 7219 or phone x2558) Course No., Credit, and Grade: 21-753, 12 Units, based on homework. Aimed at: those who have had a basic course in logic and are interested in broadening their knowledge. What is model theory: Model theory is the branch of mathematical logic which deals with relation between a formal language and its interpretations, or models. We shall study the model theory of first order predicate logic. Models are structures of the kind which arise in mathematics or computer science. To arrive at a model theory, we set up our formal language of first-order logic by specifying a list of symbols and giving rules by which sentences can be built up from the symbols. The reason for setting up a formal language is that we wish to use the sentences to reason about the models. Typical results of model theory say something about the power of expression of first-order predicate logic. Lowenheim's theorem, for example, shows that no consistent sentence can imply that a model is uncountable, or Morley's theorem shows that first order predicate logic cannot, as far as categoricity is concerned, tell the difference between one uncountable power and another. Model theory also gives methods of constructing models. A special attention will be given in this course to ultraproduct constructions and their applications in mathematics and computer science. Much of model theory deals with the interplay of syntactical and semantical ideas. ------------------------------ End of AIList Digest ********************