Date: Tue 8 Nov 1988 17:19-EST From: AIList Moderator Nick Papadakis Reply-To: AIList@AI.AI.MIT.EDU Us-Mail: MIT LCS, 545 Tech Square, Rm# NE43-504, Cambridge MA 02139 Phone: (617) 253-6524 Subject: AIList Digest V8 #123 To: AIList@AI.AI.MIT.EDU Status: R AIList Digest Wednesday, 9 Nov 1988 Volume 8 : Issue 123 Seminars: Towards a Theory of Syntactic Constructions (and more) - Arnold Zwicky Review of the First Workshop on Artificial Intelligence and Music Specialization Is For Insects - Tom Knight Generation and Recognition of Affixational Morphology - John Bear Why AI needs Connectionism? - Lokendra Shastri Writing and Reading: the View From the U.K. - John Dixon SHERLOCK: an Environment for Electronics Troubleshooting - Susanne Lajoie ---------------------------------------------------------------------- Date: Mon, 24 Oct 88 17:05:15 EDT From: rapaport@cs.Buffalo.EDU (William J. Rapaport) Subject: Towards a Theory of Syntactic Constructions (and more) - Arnold Zwicky UNIVERSITY AT BUFFALO STATE UNIVERSITY OF NEW YORK DEPARTMENT OF LINGUISTICS GRADUATE GROUP IN COGNITIVE SCIENCE and GRADUATE RESEARCH INITIATIVE IN COGNITIVE AND LINGUISTIC SCIENCES PRESENT ARNOLD ZWICKY Department of Linguistics, Ohio State University Department of Linguistics, Stanford University 1. TOWARDS A THEORY OF SYNTACTIC CONSTRUCTIONS The past decade has seen the vigorous development of frameworks for syn- tactic description that not only are fully explicit (to the point of being easily modeled in computer programs) but also are integrated with an equally explicit framework for semantic description (and, sometimes, with equally explicit frameworks for morphological and phonological description). This has made it possible to reconsider the _construc- tion_ as a central concept in syntax. Constructions are, like words, Saussurean signs--linkages of linguistic form with meanings and pragmatic values. The technical problem is to develop the appropriate logics for the interactions between construc- tions, both with respect to their form and with respect to their interpretation. I am concerned here primarily with the formal side of the matter, which turns out to be rather more intricate than one might have expected. Constructions are complexes of categories, sub- categories, grammatical relations, conditions on governed features, con- ditions on agreeing features, conditions on phonological shape, condi- tions on branching, conditions on ordering, _and_ specific contributory constructions (so that, for example, the subject-auxiliary construction in English contributes to several others, including the information question construction, as in `What might you have seen?'). The schemes of formal interaction I will illustrate are overlapping, or mutual applicability; superimposition, or invocation; and preclusion, or over- riding of defaults. Thursday, November 3, 1988 5:00 P.M. Baldy 684, Amherst Campus There will be an evening discussion on Nov. 3, 8:00 P.M., at the home of Joan Bybee, 38 Endicott, Eggertsville. ========================================================================= 2. INFLECTIONAL MORPHOLOGY AS A (SUB)COMPONENT OF GRAMMAR Friday, November 4, 1988 3:00 P.M. Baldy 684, Amherst Campus Wine and cheese to follow. Call Donna Gerdts (Dept. of Linguistics, 636-2177) for further information. ------------------------------ Date: Wed, 26 Oct 88 12:04 EDT From: "TSD::AIP1::\"Len@HEART-OF-GOLD\"%atc.bendix.com"@RELAY.CS.NET Subject: Review of the First Workshop on Artificial Intelligence and Music Date: Wed, 26 Oct 88 12:00 EDT From: Len Moskowitz Subject: Review of the First Workshop on Artificial Intelligence and Music To: "3077::IN%\"AIList@ai.ai.mit.edu\""@TSD1 Message-ID: <19881026160039.2.LEN@HEART-OF-GOLD> The First Workshop on Artificial Intelligence and Music was held on August 24, 1988 during AAAI-88. It brought together more than 40 researchers from the U.S.A, Canada, Belgium, the U.K., and Israel. The workshop was divided into five sessions: expert systems; tutoring systems and languages; cognitive models and knowledge representation; neural networks and parallelism; and a final session covering perception, philosophy, and the symbiotic relationship between music and artificial intelligence. Many of the presentations included audio/visual demonstrations. The workshop was sponsored by AAAI and organized by Mira Balaban (Ben Gurion University, Israel), Kemal Ebcioglu (IBM Thomas J. Watson Research Center), Marc Leman (University of Ghent, Belgium), and Linda Sorisio (IBM Los Angeles Scientific Center). From an AI perspective, the workshop spanned a wide range of topics including planning, machine learning, neural networks, tutoring systems, knowledge representations, languages, parallelism, pattern recognition, temporal reasoning, design, and expert systems. From a music perspective, the presenters focused on analysis of tonal and atonal music, composition, music education, music perception and cognition, performance, automated accompaniment, and user interfaces. This year's AAAI had a noteworthy event. Thanks to the AI and Music workshop and Harold Cohen's invited talk ("How to Draw Three People In a Botanical Garden," part of AAAI proper), this was the first time, to my knowledge, that research carried out within a humanities context received significant attention. Many of the attendees expressed a desire for a similar workshop at next year's IJCAI/AAAI gathering. Anyone interested in organizing or assisting next year's workshop should contact Dr. Ebcioglu (kemal@ibm.com). Copies of the workshop's proceedings are available from AAAI (445 Burgess Drive, Menlo Park, CA 94025, U.S.A.) for $20 (U.S.) plus $2.40 shipping and handling. A summary of the sessions follows: Otto Laske (New England Computer Arts Association) delivered an invited talk. Laske is perhaps the father of the AI/music synthesis and the field he's dubbed cognitive musicology. He differentiated between traditional musicology and the developing discipline of cognitive musicology in that the first is narrowly centered around the artifacts that musical creates, while the latter seeks to understand music as one of the processes and structures resulting from man's 'being in the world.' Viewed in this way, the programs we write are formal speech accounts of an activity (referents to a human activity) but not that activity. While programs are not music, they can help us to understand music. Therefore, if I understand Laske's viewpoint correctly, the goal of the AI/music synthesis is to investigate, within the music framework, how we become and are an integral part of the world. The session on expert systems included presentations describing a computer simulation of perception of musical rhythm based on Lerdahl and Jackendorff's generative theory of tonal music; a forward-chaining rule-based system that performs harmonic chord function analysis for tonal music; a system for tonal composition that learns by reordering its production rule priorities and by generalizing new rules based on recurring patterns in its histories; and a "Cybernetic Composer" that uses constraint satisfaction and backtracking to compose realistic music in four different genre's ('standard' jazz, Latin jazz, rock, and ragtime). During this last presentation, Charles Ames (Kurzweil Foundation Automated Composition Project) played a wonderfully entertaining audio tape of his system performing. The session on tutoring systems and languages included presentations about an architecture for a tutoring system to teach musical structure analysis and melody interpretation; a tutoring system to teach elementary aspects of music theory and ear training; a method of generating music using linguistic (syntactic) techniques; a preliminary description of a programming language for generating and analyzing musical compositions; and a knowledge representation for tutoring systems using constraint satisfaction embedded in a logic programming language (applied to teach harmony). The session on cognitive models and knowledge representation had presentations on modeling and generating music using multiple viewpoints based on Markov models; a representation that provides sufficient expressiveness for analysis of atonal music; and musical composition considered as problem reduction. The session on neural networks and parallelism included papers on storing and processing time-varying musical information in PDP networks; learning of musical concepts (keys, major/minor, scales, chord expectancies) and cognitive properties (pitch invariance) using neural nets; and a method of applying the massively parallel Connection Machine to separate audio sources in polyphonic music. As part of this last presentation, Barry Vercoe (MIT Media Lab) showed a videotape of an automatic accompanist that learns from rehearsal and adapts to a performer's habitual idiosyncracies. The final, rather eclectic session heard papers on the cross-fertilization between the fields of music and AI; computer implementations of a cognitive model of music perception; the use of spatial/visual representations and improved user interfaces to aid sound analysis; and the need to realize the limitations of computable functions as descriptions/simulations of music cognition. Len Moskowitz Allied-Signal Aerospace moskowitz@bendix.com (CSnet) Test Systems Division moskowitz%bendix.com@relay.cs.net (ARPAnet) Mail code 4/8 arpa!relay.cs.net!bendix.com!moskowitz (uucp) Teterboro, NJ 07608 ------------------------------ Date: Thu 3 Nov 88 11:17:04-EST From: Marc Vilain Subject: Specialization Is For Insects - Tom Knight BBN Science Development Program AI Seminar Series Lecture SPECIALIZATION IS FOR INSECTS Tom Knight MIT Artificial Intelligence Lab (tk@AI.AI.MIT.EDU) BBN Labs 10 Moulton Street 2nd floor large conference room 10:30 am, Tuesday 8 November The chaos of the last decade in parallel computer architecture is largely due to the premature specialization of parallel computer architectures to support particular programming models. The careful choice of the correct primitives to support in hardware leads to a general purpose parallel architecture which is capable of supporting a wide variety of programming models. This talk will argue that low latency communication emerges as the essential component in parallel processor design, and will demonstrate how to use low latency communication to support other programming models such as data level parallelism and coherent shared memory in large processor arrays. We are now designing a very low latency, high bandwidth, fault tolerant communications network, called Transit. It forms the communications infrastructure - the replacement of the bus - for a high speed MIMD processor array which can be programmed using a wide variety of parallel models. Transit achieves its high performance through a interdisciplinary approach to the problem of communications latency. The packaging of Transit is done using near isotropic density three dimensional wiring, allowing much tighter packing of components, and routing of wires on a 3-D grid. The network is direct contact liquid cooled with Fluorinert. The use of custom VLSI pad drivers and receivers provides very high speed signalling between chips. The topology of the network provides self-routing, fault tolerant, short pipeline delay communications between pairs of processors. And finally, the design of the processor itself allows high speed message dispatching and low latency context switch. ------------------------------ Date: Fri, 4 Nov 88 22:44:04 EST From: finin@PRC.Unisys.COM Subject: Generation and Recognition of Affixational Morphology - John Bear AI SEMINAR UNISYS PAOLI RESEARCH CENTER John Bear SRI International Generation and Recognition of Affixational Morphology Koskenniemi's two-level morphological analysis system can be improved upon by using a PATR-like unification grammar for handling the morphosyntax instead of continuation classes, and by incorporating the notion of negative rule feature into the phonological rule interpreter. The resulting system can be made to do generation and recognition using the same grammars. 1:00 am - November 7, 1988 R&D Conference Room Unisys Paoli Research Center Route 252 and Central Ave. Paoli PA 19311 -- non-Unisys visitors who are interested in attending should -- -- send email to finin@prc.unisys.com or call 215-648-7446 -- ------------------------------ Date: 4 Nov 88 15:49:33 GMT From: wucs1!loui@uunet.uu.net (Ron Loui) Subject: Why AI needs Connectionism? - Lokendra Shastri COMPUTER SCIENCE COLLOQUIUM Washington University St. Louis 4 November 1988 TITLE: Why AI needs Connectionism? A Representation and Reasoning Perspective Lokendra Shastri Computer and Information Science Department University of Pennsylvania Any generalized notion of inference is intractable, yet we are capable of drawing a variety of inferences with remarkable efficiency - often in a few hundered milliseconds. These inferences are by no means trivial and support a broad range of cognitive activity such as classifying and recognizing objects, understanding spoken and written language, and performing commonsense reasoning. Any serious attempt at understanding intelligence must provide a detailed computational account of how such inferences may be drawn with requisite efficiency. In this talk we describe some work within the connectionist framework that attempts to offer such an account. We focus on two connectionist knowledge representation and reasoning systems: 1) A connectionist semantic memory that computes optimal solutions to an interesting class of inheritance and recognition problems extremely fast - in time proportional to the depth of the conceptual hierarchy. In addition to being efficient, the connectionist realization is based on an evidential formulation and provides a principled treatment of exceptions, conflicting multiple inheritance, as well as the best-match or partial-match computation. 2) A connectionist system that represents knowledge in terms of multi-place relations (n-ary predicates), and draws a limited class of inferences based on this knowledge with extreme efficiency. The time taken by the system to draw conclusions is proportional to the length of the proof, and hence, optimal. The system incorporates a solution to the "variable binding" problem and uses the temporal dimension to establish and maintain bindings. We conclude that working within the connectionist framework is well motivated as it helps in identifying interesting classes of limited inference that can be performed with extreme efficiently, and aids in discovering constraints that must be placed on the conceptual structure in order to achieve extreme efficiency. host: Ronald Loui ------------------------------ Date: Mon 7 Nov 88 16:51:26-EST From: Marc Vilain Subject: Writing and Reading: the View From the U.K. - John Dixon BBN Science Development Program AI/EDUCATION Seminar Series Lecture WRITING AND READING: THE VIEW FROM THE U.K. John Dixon BBN Labs 10 Moulton Street 2nd floor large conference room 10:30 am, Thursday November 10 ******************************************************** * * * No abstract was available for this presentation. * * Below is a short biography of the speaker. * * * ******************************************************** John Dixon is an educational writer and consultant from London, England, who has been a teacher in an inner-city school in London as well as a Senior Lecturer in a teacher training college at Leeds. Dixon is the author of "Growth through English", the major report of the Anglo-American Dartmouth Seminar in 1966. His writing since then has included anthologies for school use and a number of books on the teaching of writing, the most recent of which is "Writing Narrative - and Beyond". For many years a member of and then chair of The Schools Council Committee on English, Dixon has directed research and studies on Teaching English to the School Leaving Age and has investigated the effect of the questions asked on university examinations on the teaching of literature in schools. ------------------------------ Date: Mon 7 Nov 88 16:52:16-EST From: Marc Vilain Subject: SHERLOCK: an Environment for Electronics Troubleshooting - Susanne Lajoie BBN Science Development Program AI Seminar Series Lecture SHERLOCK: A COACHED PRACTICE ENVIRONMENT FOR AN ELECTRONICS TROUBLESHOOTING JOB Susanne P. Lajoie Learning Research and Development Center, University of Pittsburgh (LAJOIE%LRDCA@Vms.Cis.Pittsburgh.Edu) BBN Labs 10 Moulton Street 2nd floor large conference room 10:30 am, Tuesday November 15 Sherlock is a computer-based practice environment for teaching first-term airmen avionics troubleshooting skills. Sherlock's instructional goals were determined by a cognitive task analysis of skill differences in this domain. The predominant instructional strategy is to support holistic practice of troubleshooting rather than train discrete knowledge skills. Instruction is based on complex decision graphs of skilled and less skilled plans and actions for each troubleshooting problem. As a trainee works through a problem Sherlock observes the quality of decisions the trainee makes and uses that information to provide the level of hint explicitness necessary at particular decision points in the problem. In this way, specific competency building is situated within the troubleshooting context and is sharpened to the extent that satisfies each individual's needs. Sherlock was field tested in a controlled study that compared tutored trainees with a control group that received no extra training other than "on-the-job" experience. Pre and post tests of verbal troubleshooting indicated that the tutored group performed better than the control group on post tests of troubleshooting proficiency. Not only were more problems solved but there were several indications of emerging competence over the course of tutoring that demonstrated that trainees were becoming more "expert-like" in the overall troubleshooting process. In an independent evaluation the Air Force found the Sherlock treatment to be equivalent to 47-51 months of "on the job" experience. Enhancements have been added to Sherlock that could increase its effectiveness even more. An explicit articulation of expert and student problem solving traces now exists that could facilitate the comparison process of different levels of expertise. At the completion of each problem trainees will be able to interrogate the trace of the expert problem solution and see why an expert would make a particular move as well as see the mental models used by an expert to test different paths in the problem space. ------------------------------------ This research was made possible through the combined efforts of the following individuals: Alan Lesgold, Jaya Bajpayee, Marilyn Bunzo, Gary Eggan, Linda Greenberg, Debra Logan, Thomas McGinnis, Cassandra Stanley, Arlene Weiner, Richard Wolf, and Laurie Yengo, as well as researchers at AFHRL Brooks, and the Air Force personnel that made our study possible. ------------------------------ End of AIList Digest ********************