AIList-REQUEST@SRI-AI.ARPA (AIList Moderator Kenneth Laws) (10/31/85)
AIList Digest Thursday, 31 Oct 1985 Volume 3 : Issue 160 Today's Topics: Seminars - Knowledge-Based Language Production (BBN) & Mechanical Verification of Mathematics (BBN) & Levels of Abstraction in Expert Systems (BBN) & Conversational Language System (BBN) & Correcting Misconceptions (BBN), Conferences - Economics and AI & AI Society of New England & Revised Call for Papers: OIS-86 ---------------------------------------------------------------------- Date: Thu, 31 Oct 85 00:56:16 EST From: "Steven A. Swernofsky" <SASW@MIT-MC.ARPA> Subject: Seminar - Knowledge-Based Language Production (BBN) Friday 1, November 10: 30am Room: BBN Labs, 10 Moulton Street, 3rd floor large conference room BBN Artificial Intelligence Seminar "A Knowledge-Based Approach to Language Production" Paul Jacobs The development of natural language interfaces to Artificial intelligence systems is dependent on the representation of knowledge. A major impediment to building such systems has been the difficulty in adding sufficient linguistic and conceptual knowledge to extend and adapt their capabilities. This difficulty has been apparent in systems which perform the task of language production, i. e. the generation of natural language output to satisfy the communicative requirements of a system. The problem of extending and adapting linguistic capabilities is rooted in the problem of integrating abstract and specialized knowledge and applying this knowledge to the language processing task. Three aspects of a knowledge representation system are highlighted by this problem: hierarchy, or the ability to represent relationships between abstract and specific knowledge structures; explicit referential knowledge, or knowledge about relationships among concepts used in referring to concepts; and informity, the use of a common framework for linguistic and conceptual knowledge. The knowledge based approach to language production addresses the language generation task from within the broader context of the representation and application of conceptual and linguistic knowledge. This knowledge based approach has led to the design and implementation of a knowledge representation framework, called Ace, geared towards facilitating the interaction of linguistic and conceptual knowledge in language processing. Ace is a uniform, hierarchical representation system, which facilitates the use of abstractions in the encoding of specialized knowledge and the representation of the referential and metaphorical relationships among concepts. A general purpose natural language generator, KING (Knowledge INtensive Generator), has been implemented to apply knowledge in the Ace form. The generator is designed for knowledge intensivity and incrementality, to exploit the power of the Ace knowledge in generation. The generator works by applying structured associations, or mappings, from conceptual to linguistic structures, and combining these structures into grammatical utterances. This has proven to be a simple but powerful mechanism which is relatively easy to adapt and extend. ------------------------------ Date: Thu, 31 Oct 85 02:24:17 EST From: "Steven A. Swernofsky" <SASW@MIT-MC.ARPA> Subject: Seminar - Mechanical Verification of Mathematics (BBN) Thursday 31, October 10: 30am Room: BBN Labs, 10 Moulton Street, 2nd floor large conference room BBN Laboratories Science Development Program AI Seminars Toward the Mechanical Verification of Abstract Mathematics David McAllester MIT AI Laboratory To mechanically verify a mathematical argument one must translate the argument into some formal language. Many mathematicians doubt that it will ever be practical to translate arbitrary mathematical arguments into a completely formal language. This talk will present a formal language called ONTIC which extends set theory in a way that supports an "object oriented" style of mathematical description. Ontic has been used to formally define some basic concepts of modern algebra, real analysis, and homotopy theory. We feel that any branch of modern mathematics can be concisely expressed in ONTIC. Furthermore it seems practical to translate any mathematical proof into a sequence of ONTIC formulas. A theorem- proving system has been constructed for ONTIC and some simple verifications have been done. ------------------------------ Date: 28 Oct 1985 11:01-EST From: Brad Goodman <BGOODMAN at BBNG> Subject: Seminar - Levels of Abstraction in Expert Systems (BBN) [Forwarded from the MIT bboard by SASW@MIT-MC.] Speaker: Prof. B. Chandrasekaran Laboratory for Artificial Intelligence Research Department of Computer and Information Science The Ohio State University Date: 10:30am, Monday, November 4th Place: BBN Labs, 10 Moulton Street, 3rd floor large conference room Generic Tasks in Knowledge-Based Reasoning: Characterizing and Designing Expert Systems at the "Right" Level of Abstraction We outline the elements of a framework for expert system design that we have been developing in our research group over the last several years. This framework is based on the claim that complex knowledge-based reasoning tasks can often be decomposed into a number of generic tasks each with associated types of knowledge and family of control regimes. At different stages in reasoning, the system will typically engage in one of the tasks, depending upon the knowledge available and the state of problem solving. The advantages of this point of view are manifold: (i) Since typically the generic tasks are at a much higher level of abstraction than those associated with first generation expert system languages, knowledge can be represented directly at the level appropriate to the information processing task. (ii) Since each of the generic tasks has an appropriate control regime, problem solving behavior may be more perspicuously encoded. (iii) Because of a richer generic vocabulary in terms of which knowledge and control are represented, explanation of problem solving behavior is also more perspicuous. We briefly describe six generic tasks that we have found very useful in our work on knowledge-based reasoning: classification, state abstraction, knowledge-directed retrieval, object synthesis by plan selection and refinement, hypothesis matching, and assembly of compound hypotheses for abduction. ------------------------------ Date: 28 Oct 1985 11:01-EST From: Brad Goodman <BGOODMAN at BBNG> Subject: Seminar - Conversational Language System (BBN) [Forwarded from the MIT bboard by SASW@MIT-MC.] Speaker: Prof. Janet Murray Dept. of Humanities, MIT Date: 10:30am, Tuesday, November 5th Place: BBN Labs, 10 Moulton Street, 2nd floor large conference room The Next Generation of Language Lab Materials: Developing Prototypes at MIT MIT's Athena Language Learning Project is a five-year enterprise whose aim is to develop prototypes of the next generation of language-lab materials, particularly conversation-based exercises using artificial intelligence to analyse and respond to typed input. The exercises are based upon two systematized methods of instruction that are specialties at MIT: discourse theory and simulations. The project is also seeking to incorporate two associated technologies: digital audio and interactive video. The digital audio sub-project is developing exercises for intonation practice, initially focusing on Japanese speakers learning English. The interactive video component of the project consists of preparation of a demonstration disc which features a variety of interactive video approaches including enhancement of the text-based simulations and presentation of dense conversational material in natural settings. The project is being developed on the Athena system at MIT, and is based upon the model of a near-future language lab/classroom environment that will include stations capable of providing interactive video, digital audio, and AI-based exercises. ------------------------------ Date: 28 Oct 1985 11:01-EST From: Brad Goodman <BGOODMAN at BBNG> Subject: Seminar - Correcting Misconceptions (BBN) [Forwarded from the MIT bboard by SASW@MIT-MC.] Speaker: Prof. Kathleen F. McCoy University of Delaware Date: 10:30am, Friday, November 8th Place: BBN Labs, 10 Moulton Street, 3rd floor large conference room Correcting Object Related Misconceptions Analysis of a corpus of naturally occurring data shows that users conversing with a database or expert system are likely to reveal misconceptions about the objects modelled by the system. Further analysis reveals that the sort of responses given when such misconceptions are encountered depends greatly on the discourse context. This work develops a context-sensitive method for automatically generating responses to object-related misconceptions with the goal of incorporating a correction module in the front-end of a database or expert system. The method is demonstrated through the ROMPER system (Responding to Object-related Misconceptions using PERspective) which is able to generate responses to two classes of object-related misconceptions: misclassifications and misattributions. The transcript analysis reveals a number of specific strategies used by human experts to correct misconceptions, where each different strategy refutes a different kind of support for the misconception. In this work each strategy is paired with a structural specification of the kind of support it refutes. ROMPER uses this specification, and a model of the user, to determine which kind of support is most likely. The corresponding response strategy is then instantiated. The above process is made context sensitive by a proposed addition to standard knowledge-representation systems termed "object perspective." Object perspective is introduced as a method for augmenting a standard knowledge-representation system to reflect the highlighting affects of previous discourse. It is shown how this resulting highlighting can be used to account for the context-sensitive requirements of the correction process. ------------------------------ Date: Wed 30 Oct 85 21:23:18-PST From: Ken Laws <Laws@SRI-AI.ARPA> Subject: Conference - Economics and AI See Communications of the ACM, September 1985, p. 1008, for an announcement of the 1st Int. Conf. on Economics and AI (including management science, organizational and behavioral sciences, etc.), to be held in Aix-en-Provence, France, on September 2-4, 1986. ------------------------------ Date: Tue 29 Oct 85 20:13:44-EST From: Michael Lebowitz <LEBOWITZ@CS.COLUMBIA.EDU> Subject: Conference - AI Society of New England THE SEVENTH ANNUAL CONFERENCE OF THE ARTIFICIAL INTELLIGENCE SOCIETY OF NEW ENGLAND NOVEMBER 1-2, 1985, BRANDEIS UNIVERSITY, WALTHAM, MA NATHAN SEIFER AUDITORIUM, IN FORD HALL Friday, November 1, 1985 8:00 PM Invited talk by Drew McDermott (Yale University) Easy and Hard Problems in Artificial Intelligence Abstract -- AI has not exactly solved everything. In fact, the more we progress the harder problems we uncover. However, some supposedly hard problems look as if they will evaporate completely. In this talk I will discuss: ancient problems that now look easy, like free will and consciousness; modern problems that are hard, like representing spatial knowledge; ancient problems that are still hard, like the nature of explanation and induction. 9:00 PM Traditional AISNE social hour Saturday, November 2, 1985 10:00 AM 15 minute talks Robert McCartney (Brown University) Algorithmic Synthesis Tom Ellman (Columbia University) Explanation Based Generalization of Logic Circuit Designs Dave Glaubman (Northeastern University) A Novice System for Bidding in Bridge Robert S. Rist (Yale University) Plans in Programming Brian Otis (University of New Hampshire) Knowledge-based Guidance for an Autonomous Underwater Vehicle 11:30 AM Panel chaired by John Kender (Columbia University) Are Vision and Robotics AI? 12:30 PM Lunch Break 2:00 PM more 15 minute talks Henry A. Kautz (University of Rochester) Plan Recognition as Theory Formation Mary P. Harper (Brown University) Tense and Time in English Tony Maddox (Brandeis University) A Parallel Approach to Generating Visual Event Descriptions Marie Vaughan (University of Massachusetts) Rewriting and Regeneration: A Computational Model of the Writing Process Ben Moreland (University of Connecticut) Artificial Ingelligence Research at UConn 3:30 PM still more 15 minute talks Marie Bienkowski (Princeton University) Generation of Elaborations: A Goal-Directed Model Steven Hanks (Yale University) Temporal Reasoning and Default Logic Hon Wai Chun (Brandeis University) Progress Towards Massively Parallel Speech Recognition Richard N. Pelavin (University of Rochester) A Formal Logic that Supports Planning with a Partial Description of the Future 4:30 PM AISNE business meeting -- volunteers for organizing next year's conference will be solicited. There is no registration fee for AISNE, but a small donation is requested to cover the costs of the Friday night social hour. Program chairman: Local arrangements: Professor Michael Lebowitz Tony Maddox Department of Computer Science Brandeis University 450 Computer Science Building Computer Science Department Columbia University Ford Hall 3-227 New York, NY 10027 Waltham, MA 02254 212-280-8196 617-647-2119 lebowitz@columbia-20.arpa tony%brandeis@csnet ------------------------------ Date: Tue, 29 Oct 85 11:26 EST From: Hewitt@MIT-MC.ARPA Subject: REVISED call for papers: OIS-86 ******************* C A L L F O R P A P E R S * * ---------------------------------------------- * * Third ACM Conference On * * OFFICE INFORMATION SYSTEMS * OIS-86 * * * October 6-8, 1986 * * Biltmore Plaza Hotel * * Providence, RI ******************* ------------------------------------------------- General Chair: Carl Hewitt, Topics appropriate for this MIT conference include (but are not restricted to) the following as they Program Chair: Stanley Zdonik, relate to OIS: Brown University Technologies including Display, Voice, Treasurer: Gerald Barber, Telecommunications, Print, etc. Gold Hill Computers Human Interfaces Local Arrangements: Andrea Skarra, Brown University Deployment and Evaluation An interdisciplinary conference on System Design and Construction issues relating to office information systems (OIS) sponsored Goals and Values by ACM/SIGOA in cooperation with Brown University and the MIT Distributed Services and Applications Artificial Intelligence Laboratory. Submissions from the following Knowledge Bases and Reasoning fields are solicited: Distributed Services and Applications Anthropology Artificial Intelligence Indicators and Models Cognitive Science Computer Science Needs and Organizational Factors Economics Management Science Impact of Computer Integrated Psychology Manufacturing Sociology The following have confirmed their membership on the program committee: Guiseppe Attardi Ray Panko University of Pisa University of Hawaii James Bair Robert Rosin Hewlett Packard Syntrex Gerald Barber Erik Sandewall Gold Hill Computers Linkoping University Peter de Jong Walt Scacci MIT USC Irene Greif Andrea Skarra MIT Brown University Sidney Harris Susan Leigh Star Georgia State University Tremont Research Institute Carl Hewitt Luc Steels MIT University of Brussels Heinz Klein Sigfried Treu SUNY University of Pittsburgh Fred Lochovsky Dionysis Tsichritzis University of Toronto University of Geneva Fanya Montalvo Eleanor Wynn MIT Brandon Interscience Naja Naffah Aki Yonezawa Bull Transac Tokyo Institute of Technology Margrethe Olson Stanley Zdonik NYU Brown University The invited keynote speaker is Professor J.C.R. Licklider of MIT. Unpublished papers of up to 5000 words (20 double-spaced pages) are sought. The first page of each paper must include the following information: title, the author's name, affiliations, complete mailing address, telephone number and electronic mail address where applicable, a maximum 150-word abstract of the paper, and up to five keywords (important for the correct classification of the paper). If there are multiple authors, please indicate who will present the paper at OIS-86 if the paper is accepted. Proceeedings will be distributed at the conference and will later be available from ACM. Selected papers will be published in the ACM Transactions on Office Information Systems. Please send eight (8) copies of the paper to: Prof. Stan Zdonick OIS-86 Program Chair Computer Science Department Brown University P.O. Box 1910 Providence, RI 02912 DIRECT INQUIRIES TO: Margaret H. Franchi (401) 863-1839. IMPORTANT DATES Deadline for Paper Submission: February 1, 1986 Notification of Acceptance: April 30, 1986 Deadline for Final Camera-Ready Copy: July 1, 1986 Conference Dates: October 6-8, 1986 ------------------------------ End of AIList Digest ********************