nl-kr-request@cs.rpi.edu (NL-KR Moderator Chris Welty) (03/22/89)
NL-KR Digest (Tue Mar 21 14:59:45 1989) Volume 6 No. 10 Today's Topics: Abstracts from Journal of Exp. and Theor. AI BBN AI Seminar: Karen Srachik visiting appt. at SUNY Buffalo MT Proceedings talks at UT Austin Center for CogSci Bar-Ilan Symposium on Foundations of AI Submissions: nl-kr@cs.rpi.edu Requests, policy: nl-kr-request@cs.rpi.edu Back issues are available from host archive.cs.rpi.edu [128.213.1.10] in the files nl-kr/Vxx/Nyy (ie nl-kr/V01/N01 for V1#1), mail requests will not be promptly satisfied. If you can't reach `cs.rpi.edu' you may want to use `turing.cs.rpi.edu' instead. --------------------------------------------------------- To: nl-kr@cs.rpi.edu >From: cfields@NMSU.Edu Date: Fri, 3 Mar 89 17:17:17 MST Subject: Abstracts from Journal of Exp. and Theor. AI _________________________________________________________________________ The following are abstracts of papers appearing in the inaugural issue of the Journal of Experimental and Theoretical Artificial Intelligence. JETAI 1, 1 was published 1 January, 1989. For submission information, please contact either of the editors: Eric Dietrich Chris Fields PACSS - Department of Philosophy Box 30001/3CRL SUNY Binghamton New Mexico State University Binghamton, NY 13901 Las Cruces, NM 88003-0001 dietrich@bingvaxu.cc.binghamton.edu cfields@nmsu.edu JETAI is published by Taylor & Francis, Ltd., London, New York, Philadelphia _________________________________________________________________________ Minds, machines and Searle Stevan Harnad Behavioral & Brain Sciences, 20 Nassau Street, Princeton NJ 08542, USA Searle's celebrated Chinese Room Argument has shaken the foundations of Artificial Intelligence. Many refutations have been attempted, but none seem convincing. This paper is an attempt to sort out explicitly the assumptions and the logical, methodological and empirical points of disagreement. Searle is shown to have underestimated some features of computer modeling, but the heart of the issue turns out to be an empirical question about the scope and limits of the purely symbolic (computational) model of the mind. Nonsymbolic modeling turns out to be immune to the Chinese Room Argument. The issues discussed include the Total Turing Test, modularity, neural modeling, robotics, causality and the symbol-grounding problem. _________________________________________________________________________ Explanation-based learning: its role in problem solving Brent J. Krawchuck and Ian H. Witten Knowledge Sciences Laboratory, Department of Computer Science, University of Calgary, 2500 University Drive, NW, Calgary, Alta, Canada, T2N 1N4. `Explanation-based' learning is a semantically-driven, knowledge-intensive paradigm for machine learning which contrasts sharply with syntactic or `similarity-based' approaches. This paper redevelops the foundations of EBL from the perspective of problem-solving. Viewed in this light, the technique is revealed as a simple modification to an inference engine which gives it the ability to generalize the conditions under which the solution to a particular problem holds. We show how to embed generalization invisibly within the problem solver, so that it is accomplished as inference proceeds rather than as a separate step. The approach is also extended to the more complex domain of planning to illustrate that it is applicable to a variety of logic-based problem-solvers and is by no means restricted to only simple ones. We argue against the current trend to isolate learning from other activity and study it separately, preferred instead to integrate it into the very heart of problem solving. - --------------------------------------------------------------------------- The recognition and classification of concepts in understanding scientific texts Fernando Gomez and Carlos Segami Department of Computer Science, University of Central Florida, Orlando, FL 32816, USA. In understanding a novel scientific text, we may distinguish the following processes. First, concepts are built from the logical form of the sentence into the final knowledge structures. This is called concept formation. While these concepts are being formed, they are also being recognized by checking whether they are already in long-term memory (LTM). Then, those concepts which are unrecognized are integrated in LTM. In this paper, algorithms for the recognition and integration of concepts in understanding scientific texts are presented. It is shown that the integration of concepts in scientific texts is essentially a classification task, which determines how and where to integrate them in LTM. In some cases, the integration of concepts results in a reclassification of some of the concepts already stored in LTM. All the algorithms described here have been implemented and are part of SNOWY, a program which reads short scientific paragraphs and answer questions. - -------------------------------------------------------------------------- Exploring the No-Function-In-Structure principle Anne Keuneke and Dean Allemang Laboratory for Artificial Intelligence Research, Department of Computer and Information Science, The Ohio State University, 2036 Neil Avenue Mall, Columbus, OH 43210-1277, USA. Although much of past work in AI has focused on compiled knowledge systems, recent research shows renewed interest and advanced efforts both in model-based reasoning and in the integration of this deep knowledge with compiled problem solving structures. Device-based reasoning can only be as good as the model used; if the needed knowledge, correct detail, or proper theoretical background is not accessible, performance deteriorates. Much of the work on model-based reasoning references the `no-function-in-structure' principle, which was introduced be de Kleer and Brown. Although they were all well motivated in establishing the guideline, this paper explores the applicability and workability of the concept as a universal principle for model representation. This paper first describes the principle, its intent and the concerns it addresses. It then questions the feasibility and the practicality of the principle as a universal guideline for model representation. ___________________________________________________________________________ ------------------------------ To: nl-kr@cs.rpi.edu Date: Wed 15 Mar 89 23:11:07-EST >From: Marc Vilain <MVILAIN@G.BBN.COM> Subject: BBN AI Seminar: Karen Srachik BBN Science Development Program AI Seminar Series Lecture VISUAL NAVIGATION: CONSTRUCTING AND UTILIZING SIMPLE MAPS OF AN INDOOR ENVIRONMENT Karen Sarachik MIT Artificial Intelligence Laboratory (kbs@wheaties.ai.mit.edu) BBN Labs 10 Moulton Street 2nd floor large conference room 10:30 am, Tuesday March 21 Much work with mobile robots has been done in the past using both vision and sonar to build maps, or, given a map, to successfully plan and execute trajectories to a goal. The most successful examples of robot navigation occurred in carefully engineered environments where the robot was able to accurately predict what its sensory input should be at any point, and correct for drift by comparing actual input to the projected input. In unstructured environments, however, the problem became much harder, and the obvious approaches failed to produce good results. The problem is further complicated by the fact that most interesting environments are not static, but rather are changing continually. In this talk I will discuss the problem from a different angle altogether, using the way people navigate through buildings as insight and inspiration. The goal is to navigate through an office environment using only visual information gathered from four cameras, whose initial detailed configuration is not known, placed onboard a mobile robot. The method is insensitive to physical changes within the room it is inspecting, such as moving objects. The map is built without the use of odometry or trajectory integration, which are often unreliable. At the heart of this technique is the development of a ``room recognizer'' which is able to deduce the size and shape of a room in conjunction with a ``door recognizer'' which recognizes a potential door by finding two vertical edges close enough together. The long term goal of the project described here is for the robot to build simple maps of its environment, presumed to be a single floor of an office building, and to localize itself within this framework. - ------ ------------------------------ To: nl-kr@cs.rpi.edu Date: Wed, 8 Mar 89 12:29:49 EST >From: rapaport@cs.Buffalo.EDU (William J. Rapaport) Subject: visiting appt. at SUNY Buffalo ========================================================================= VISITING INSTRUCTIONAL POSITION DEPARTMENT OF COMPUTER SCIENCE SUNY AT BUFFALO We have an opening for a Visiting Lecturer or Visiting Assistant Professor for the 1989/90 Academic Year, the title depending on credentials. The teaching load would be two courses per semester, and the salary would be $28,000 plus benefits. Send a c.v. and names of four references to: Ms. Helene Kershner, Assistant Chairman, Department of Computer Science, SUNY at Buffalo, 226 Bell Hall, Buffalo, NY 14260-7022; or to kershner@cs.buffalo.edu. For full consideration, applications should be received by April 1, 1989. SUNY is an affirmative action/equal opportunity employer. ------------------------------ To: nl-kr@cs.rpi.edu Date: Thu, 9 Mar 89 14:36:15 +0100 >From: Klaus Schubert <dlt1!schubert@nluug.nl> Phone: +31 30 911911 Telex: 40342 bso nl Subject: MT Proceedings ************* BOOK ANNOUNCEMENT **** BOOK ANNOUNCEMENT ************************ Recently published: NEW DIRECTIONS IN MACHINE TRANSLATION Conference proceedings, Budapest 18-19 August 1988. Edited by Dan Maxwell, Klaus Schubert and Toon Witkam. [= Distributed Language Translation 4] Dordrecht / Providence: Foris Publications, 1988, 259 pp. Available from Foris Publications Postbus 509 NL-3300 AM Dordrecht Netherlands Distributor for the USA and Canada: Foris Publications USA P. O. Box 5904 Providence RI 02903 USA Distributor for Japan: Toppan Company Sufunomoto Bldg. 1-6, Kanda Surugadai Chiyoda-ku Tokyo 101 Japan ******************************************************************************* C O N T E N T S W. John HUTCHINS (Norwich, Great Britain): Recent developments in machine translation Tibor V'AMOS (Budapest, Hungary): Language and the computer society Ivan I. OUBINE / Boris D. TIKHOMIROV (Moscow, Soviet Union): The state of the art in machine translation in the U.S.S.R. DONG Zhen Dong (Peking, China): MT research in China Christian BOITET (Grenoble, France): Pros and cons of the pivot and transfer approaches in multilingual machine translation Michiko KOSAKA / Virginia TELLER / Ralph GRISHMAN (New York, USA): A sublanguage approach to Japanese-English machine translation Iv'an GUZM'AN DE ROJAS (La Paz, Bolivia): ATAMIRI - interlingual MT using the Aymara language Klaus SCHUBERT (Utrecht, Netherlands): The architecture of DLT - interlingual or double direct? Christa HAUENSCHILD (Berlin, F.R.Germany): Discourse structure \(mi some implications for machine translation Jun-ichi TSUJII (Kyoto, Japan [now Manchester, Great Britain]): What is a cross-linguistically valid interpretation of discourse? Christian GALINSKI (Vienna, Austria): Advanced terminology banks supporting knowledge-based MT Wera BLANKE (Berlin, German D.R.): Terminologia Esperanto-Centro - efforts for terminological standardization in the planned language Dietrich M. WEIDMANN (Schaffhausen, Switzerland): Universal applicability of dependency grammar Bengt SIGURD (Lund, Sweden): Translating to and from Swedish by SWETRA - a multilanguage translation system G'abor PR'OSZ'EKY (Budapest, Hungary): Hungarian - a special challenge to machine translation? Claude PIRON (Geneva, Switzerland): Learning from translation mistakes Petr SGALL (Prague, Czechoslovakia): On some results of the conference Index ------------------------------ To: nl-kr@cs.rpi.edu Date: Fri 17 Mar 89 09:41:41-CST >From: Kent Wittenburg <HI.WITTENBURG@MCC.COM> Subject: talks at UT Austin Center for CogSci Colloquium, Center for Cognitive Science, Linguistics Department, University of Texas at Austin When: Monday, March 20, 3:30 PM Where: GRG 220, U.T. campus PARSING AS A RACE Graeme Hirst Department of Computer Science University of Toronto Abstract: We present a processing model that integrates some important psychological claims about the human sentence parsing mechanism, namely that processing is influenced by limitations on working memory and by various syntactic preferences. The model uses time-constraint information to resolve conflicting preferences in a psychologically plausible way. The starting point for this proposal is the Sausage Machine model (Frazier and Fodor, 1978; Fodor and Frazier, 1980). From there, we attempt to overcome the original model's dependence on ad hoc aspects of its grammar, and its omission of verb-frame preferences. We also add mechanisms for lexical disambiguation and semantic processing in parallel with syntactic processing. [This paper is co-authored with Susan McRoy.] - ------------------------------------------- Colloquium, Human Interface Laboratory, MCC When: Tuesday, March 21, 10:30 AM Where: ACA conference room, MCC Balcones Research Center, Austin TX KNOWLEDGE REPRESENTATION PROBLEMS IN NATURAL LANGUAGE UNDERSTANDING Graeme Hirst Department of Computer Science University of Toronto Abstract: In artificial intelligence these days, just about anything that's any good is `knowledge-based'. Consequently, knowledge representation formalisms are big business, and are available in a wide range of styles and colors to suit the various demands of consumers in the marketplace. I want to argue that consumers in the natural language understanding research community are not as well served as they might be, and many of their needs have been overlooked. I will investigate exactly what is required of a KR in these roles in NLU, where some of the problems lie, and where we might look for some of the solutions. I take as a starting point the idea that we need a structured representation with a denotational semantics. I assume that, other things being equal, a compositional representation is to be preferred -- that is, a representation in which the meaning of the whole is a systematic function of the meaning of the parts from which it is constructed. For example, if we have representations of "on Tuesday" and "Ross kissed Nadia" we could combine them in some fairly obvious way to get the representation of "Ross kissed Nadia on Tuesday". I will discuss work in my research group on these issues, including the semantics of focusing adverbs, the representation of ambiguities of description, and the representation of ontological assertions. I will give little time to issues of tractability (cf. Levesque and Brachman), but rather emphasize questions that are prior to such issues. Also, I won't address problems in representations that just try to describe the world or the laws of physics or commonsense (Hayes, Lenat, Hobbs, etc.). - ------ ------------------------------ To: nl-kr@cs.rpi.edu Date: Sun, 12 Mar 89 17:02:59 IDT >From: GOLUMBIC%ISRAEARN.BITNET@CUNYVM.CUNY.EDU Subject: Bar-Ilan Symposium on Foundations of AI *** Second Announcement *** Bar-Ilan Symposium on the Foundations of Artificial Intelligence 19-21 June 1989 Sponsored by the Research Institute for the Mathematical Sciences Bar-Ilan University, Ramat Gan, Israel Invited speakers: John McCarthy (Stanford University) "Formalized Common Sense Knowledge and Reasoning" Ronald Rivest (M.I.T.) "Recent Developments in Machine Learning Theory" Joseph Halpern (IBM Research) "Reasoning about Knowledge and Probability" ................................................................ The Annals of Mathematics and Artificial Intelligence will publish a special issue, containing selected refereed full length papers, as a permanent record of the Symposium. These should be submitted shortly after the conclusion of the Symposium and be at the standard of the best professional journals. High quality research papers are solicited for consideration by the program committee to be presented at the Symposium. Submission of extended abstracts should be sent by 31 March 1989 in triplicate to: Prof. Martin Golumbic BISFAI-89 Program Chair IBM Israel Scientific Center Technion City Haifa, Israel or by electronic mail to: golumbic@israearn.bitnet Decisions on talks will be made within one month of receipt. ................................................................ The Bar-Ilan Symposium on the Foundations of Artificial Intelligence is intended to become a biennial event which will focus on a range of topics of concern to scholars applying quantitative, combinatorial, logical, algebraic and algorithmic methods to AI areas as diverse as decision support, automatic reasoning, knowledge-based systems, machine learning, computer vision, and robotics. These include applied logicians, algorithms and complexity researchers, AI theorists, and applications specialists using mathematical methods. By sponsoring such symposia, we hope to influence the spawning of new areas of applied mathematics and the strengthening of the scientific underpinnings of artificial intelligence. ............ REGISTRATION AND HOTEL ACCOMODATIONS ........ We have reserved a block of hotel accommodations at the Kfar Hamaccabia Hotel in Ramat Gan, a first-class hotel which also has sports facilities available gratis for the Symposium participants. The Symposium will take place at the University, which is a short ride, or a half-hour walk, from the hotel. The room rate is $44 single or $54 double (including breakfast). Reservations must be made DIRECTLY WITH THE AGENT Sharon Tours, Attn: Ms. Dennis, P.O.Box 2605, Ramat Gan, Israel Tel: 972-3-738144 FAX: 972-3-724365 mentioning the Bar-Ilan Symposium. To allow the organizers to reserve sufficient lecture room space, please fill in and return this portion of the form to Dr. Ariel Frank, BISFAI-89 Organizing Chair Department of Mathematics and Computer Science Bar-Ilan University, Ramat Gan, ISRAEL (email: ariel@bimacs.bitnet) ________________________________________________________________ ****** PLEASE RETURN THIS FORM ********* Name: ________________________________________________________ Affiliation: _________________________________________________ Address: _____________________________________________________ Electronic mail: ____________________________________________ _____ I will attend the Bar-Ilan Symposium June 19-21, 1989 _____ Please send me the third announcement in May 1989. I do / do not plan to submit a paper. ------------------------------ End of NL-KR Digest *******************