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AIList Digest Volume 4 Issue 172
AIList Digest Thursday, 24 Jul 1986 Volume 4 : Issue 172
Today's Topics:
Seminars - COPYCAT: Modeling Creative Analogical Thought (Ames) &
DB and KB Interface for Structural Engineering (CMU) &
Automatic Debugging for Intelligent Tutoring Systems (UTexas) &
Our Cognitive Abilities Limit the Power of AI (SRI),
Workshop - Uncertainty in Knowledge-Based Systems,
Conference - 2nd AI Applications in Engineering
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Date: Mon, 21 Jul 86 11:18:22 pdt
From: eugene@AMES-NAS.ARPA (Eugene Miya)
Subject: Seminar - COPYCAT: Modeling Creative Analogical Thought (Ames)
National Aeronautics and Space Administration
Ames Research Center
SEMINAR ANNOUNCEMENT
Joint RCR Branch / Ames AI Forum Seminar
SPEAKER: Douglas Hofstadter
Cognitive Science
University of Michigan
TOPIC: THE COPYCAT PROJECT: MODELING CREATIVE ANALOGICAL THOUGHT
The fluidity inherent in concepts in the human mind allows different
situations to be mapped onto each other and a type of translation set up
between them. Every analogy (i.e., mapping of this sort) involves some degree
of stress, and the more stress there is, the weaker the analogy is. For an
analogy to be created, there must be mechanisms that gauge the stress of any
tentative mapping. We consider the central mechanism to be an unconscious
mental metric (i.e., a type of distance relation between concepts), which
allows the mind to quickly sense close resemblances and to accept them as
valid "equations" making up part of the translation between situations, and
which conversely makes the mind balk at far-fetched "equations" and give up
on translations that cause too much stress.
In the Copycat project, the network embodying this metric is called the
"slipnet" -- the idea being that the proximity of two nodes in the slipnet
indicates the propensity of the corresponding concepts to "slip" into each
other. Copycat's slipnet is the core of our effort at modeling "creative
slippage", which we feel is how deep and insightful analogies come about.
We have carefully tailored the domain in which the Copycat program operates,
so that it contains all the essential qualities -- but no extra qualities --
of a domain in which highly creative (as well as highly mundane) analogies
can be made.
Ultimately, however, our project is not so much about analogies per se,
but about human concepts and how they are structured so as to form something
like a slipnet. In that sense, analogies are merely an instrument for us.
Any analogy created by a human reveals some aspects of a human slipnet, which
we then attempt to transfer to our model. Conversely, the analogies created
by the Copycat program reveal the accuracy of our artificial slipnet, and thus
of our model of concepts.
In summary, the Copycat project is an attempt to study the basis for the
fluidity of the human mind by exploring the world of creative analogies within
a carefully limited domain.
DATE: Wednesday, TIME: 1:00 - 2:00 pm BLDG. 201 Main Auditorium
July 30, 1986
POINT(S) OF CONTACT: Eugene Miya PHONE NUMBER: (415) 694-6453
NET ADDRESS: eugene@ames-nas.arpa
or Alison Andrews (415) 694-6741 andrews%ear@ames-io.arpa
VISITORS ARE WELCOME: Register and obtain vehicle pass at Ames Visitor
Reception Building (N-253) or the Security Station near Gate 18. Do not
use the Navy Main Gate.
Non-citizens (except Permanent Residents) must have prior approval from the
Director's Office one week in advance. Submit requests to the point of
contact indicated above. Non-citizens must register at the Visitor
Reception Building. Permanent Residents are required to show Alien
Registration Card at the time of registration.
------------------------------
Date: 21 Jul 86 10:19:22 EDT
From: Craig.Howard@cive.ri.cmu.edu
Subject: Seminar - DB and KB Interface for Structural Engineering (CMU)
FINAL PUBLIC ORAL EXAMINATION
for the degree of
DOCTOR OF PHILOSOPHY
Candidate: H. Craig Howard
Title of Dissertation: Interfacing Databases and Knowledge-Based Systems
for Structural Engineering Applications
Department: Civil Engineering
Time: 1:00 pm Tuesday, July 22, 1986
Place: Adamson Wing - Baker Hall
Database management systems and expert systems will be important components
of integrated computer-aided design systems. A powerful, adaptable
interface between these components is necessary to build an integrated
structural engineering computing environment. The thesis examines the basic
issues involved in interfacing expert systems with database management
systems and describes the architecture of a prototype system, KADBASE.
KADBASE is a flexible, knowledge-based interface in which multiple expert
systems and multiple databases can communicate as independent,
self-descriptive components within an integrated, distributed engineering
computing system. The thesis presents examples from three knowledge-based
systems to demonstrate the use of KADBASE in typical engineering design
applications.
------------------------------
Date: Mon 21 Jul 86 17:27:12-CDT
From: Bill Murray <ATP.Murray@R20.UTEXAS.EDU>
Subject: Seminar - Automatic Debugging for Intelligent Tutoring Systems
(UTexas)
I will be giving the following talk on Thursday from 12 to 1 in
Taylor 3.128. All graduate students and faculty are invited. Bring
your lunch if you like.
Automatic Program Debugging for Intelligent Tutoring Systems
by
William Murray
Program debugging is an important part of the domain expertise
required for intelligent tutoring systems that teach programming
languages. This talk explores the process by which student programs can
be automatically debugged in order to increase the instructional
capabilities of these systems. The research presented provides a
methodology and implementation for the diagnosis and correction of
nontrivial recursive programs. In this approach, recursive programs are
debugged by repairing induction proofs in the Boyer-Moore Logic.
The potential of a program debugger to automatically debug widely
varying novice programs in a nontrivial domain is proportional to its
capabilities to reason about computational semantics. By increasing
these reasoning capabilities a more powerful and robust system can
result. This research supports these claims by discussing the design,
implementation, and evaluation of Talus, an automatic debugger for LISP
programs and by examining related work in automated program debugging.
Talus relies on its abilities to reason about computational semantics
to perform algorithm recognition, infer code teleology and to
automatically detect and correct nonsyntactic errors in student programs
written in a restricted, but nontrivial, subset of LISP. Solutions can
vary significantly in algorithm, functional decomposition, role of
variables, data flow, control flow, values returned by functions, LISP
primitives used, and identifiers used. Solutions can consist of
multiple functions, each containing multiple bugs. Empirical evaluation
demonstrates that Talus achieves high performance in debugging widely
varying student solutions to challenging tasks.
------------------------------
Date: Wed 23 Jul 86 12:12:25-PDT
From: Amy Lansky <LANSKY@SRI-WARBUCKS.ARPA>
Subject: Seminar - Our Cognitive Abilities Limit the Power of AI (SRI)
OUR COGNITIVE ABILITIES LIMIT THE POWER OF AI
Jack Alpert (ALPERT@SCORE)
Stanford Knowledge Integration Lab
and
School of Education, Stanford University
11:00 AM, MONDAY, July 28
SRI International, Building E, Room EK228
"Expert Systems: How far can they go?" was a panel topic at AAAI
1985. Brian Smith described the limits of AI in terms of the
programmer's ability to know if his encoded model reflected the world
that his expert system was to manage. "We have no techniques.. to
study the ... relationship between model and world. We are unable...
to assess the appropriateness of models, or to predict when models
fail."
Most of us with icy road experience are convinced we know how to
recover from skids. In the talk I will prove that our skid recovery
algorithms work only on a small set of possible skids. Skids that lie
outside of this small set result in accidents. Our "inappropriate"
skid recovery models cause accidents. 20 years of driving experience
does not revile the skid model's limitations. When we have been
building expert systems for 20 years, why should we be any better
prepared to perceive model inappropriateness?
The limited set of cognitive abilities that most people develop cannot
identify domains where models fail. I describe a temporal cognitive
ability most of us lack. Given the definition of such an ability, I
will briefly describe a line of research that explains why people
never develop the ability. Should this research be successful, we
will create new learning environments that enhance first cognitive
abilities, then modeling, and finally the power of AI systems.
VISITORS: Please arrive 5 minutes early so that you can be escorted up
from the E-building receptionist's desk. Thanks!
------------------------------
Date: Thu, 24 Jul 86 12:21:25 edt
From: Beth Adelson <adelson@YALE.ARPA>
Subject: Workshop - Uncertainty in Knowledge-Based Systems
Forwarded from Ron Yager:
A workshop will be held at the AAAI meeting entitled
"Dealing with Uncertainty in Knowledge-Based Systems".
An open discussion.
Date: Thursday August 14.
Time: 9 am - noon.
Place: Richter Hall, Room 2
The workshop will be a lively open discussion on issues related to the
management of uncertainty. A number of prominent workers in the field
will attend and act as focal points.
All are invited to participate.
For further information contact:
Ronald R. Yager
(212) 249-2047
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Date: Thu, 24 Jul 86 09:30:46 -0500
From: sriram@ATHENA.MIT.EDU
Subject: Conference - 2nd AI Applications in Engineering
CALL FOR PAPERS
SECOND INTERNATIONAL CONFERENCE ON
APPLICATIONS OF ARTIFICIAL INTELLIGENCE IN
ENGINEERING
AUGUST 4TH-7TH, 1987
BOSTON, MASSACHUSETTS
INTRODUCTION
Following the success of the first international conference in
Southampton, UK, the second international conference is to be held in
Boston during the first week of August. The first international
conference stimulated many presentations on both the tools and
techniques required for the successful use of AI in engineering and
many new applications. The organizing committee members anticipate
that the second conference will be even more succesful and encourage
papers to be submitted.
OBJECTIVES
The purpose of this conference is to provide an international forum
for the presentation of work on the applications of artificial
intelligence to engineering problems. It also aims to encourage and
enhance the development of this most important area of research.
CONFERENCE THEMES
The following topics are suggested and other related areas will be
considered:
- Computer-aided design
- Planning and scheduling
- Constraint management
- Intelligent tutors
- Knowledge-based systems
- Knowledge representation
- Learning
- Natural language applications
- Cognitive modelling of engineering problems
- Database interfaces
- Graphical interfaces
- Knowledge-based simulation
- Model-based problem solving
SUBMISSION REQUIREMENTS
Authors are invited to submit a 1000 word extended abstract. This
abstract should have sufficient details, such as the type of knowledge
representation, problem solving strategies, and the implementation
language used, to permit evaluation by a committee consisting of
renowned experts in the field. The abstract should be accompanied by
the following details: author's name, address, affiliation, and the
person to whom all correspondence should be sent.
All abstracts should be submitted to Dr. R. Adey, Computational
Mechanics Inc., Suite 6200, 400 West Cummings Park, Woburn, MA 01801
(Tel. no. 617-933-7374), before November 1986. The notification of
acceptance will be sent before February 1st, 1987. Final acceptance
of papers will be based on the review of the complete paper.
Organizing Committee
General Chair Dr. R. Adey, CML Ltd.
Program Chair Dr. J. Connor, M. I. T.
Technical Chair Dr. D. Sriram, M. I. T.
Technical Program Co-ordinators
Dr. M. Tenenbaum, Fairchild Research Labs, USA
Dr. R. Milne, Intelligent Applications Ltd., UK
Dr. J. Gero, University of Sydney, Australia
Advisory Board
Leading researchers in the field
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End of AIList Digest
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