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AIList Digest Volume 3 Issue 160
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
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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
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End of AIList Digest
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