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AIList Digest Volume 4 Issue 148
AIList Digest Thursday, 12 Jun 1986 Volume 4 : Issue 148
Today's Topics:
Queries - Tools for RSX & Organic Chemistry &
Russian Paper on Sequencing Problems & Scheme &
Neural Nets & Complexity Theory &
Creativity and Analogy & AI and Education
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Date: Mon 9 Jun 86 09:22:49-PDT
From: JPENNINO@USC-ECL.ARPA
Subject: TOOLS FOR RSX??
Does anyone know of any ai tools/languages that run under RSX other
than the two versions of LISP in DECUS?
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Date: Tue, 10 Jun 86 13:24 EDT
From: John Batali <BATALI@OZ.AI.MIT.EDU>
Subject: AI & Organic Chemistry
I'd like to find out about any AI projects attempting to hack organic
chemistry. I would be interested in information about systems which do
inorganic and biochemistry also. I know about DENDRAL. Please reply to
me and I will collect results and send them to the list.
John Batali
BATALI@OZ.AI.MIT.EDU
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Date: Tue, 10 Jun 86 11:10 EST
From: MUKHOP%RCSJJ%gmr.com@CSNET-RELAY.ARPA
Subject: Russian to English translation
I would like to obtain an English translation of:
"Some exact and Approximate Algorithms for Solution of Some
Sequencing Problems with Constraints", Kibernetika (Kiev), 1985, #3,
pp 29-33. The paper is in Russian with an English summary. I do not
have a copy of the paper. Any help will be greatly appreciated.
Uttam Mukhopadhyay
Computer Science Dept.
GM Research Labs
Warren, MI 48090-9057
(313)575-2105
Net address: mukhop@gmr.com
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Date: Tue 10 Jun 86 08:29:38-PDT
From: Mark Richer <RICHER@SUMEX-AIM.ARPA>
Subject: Scheme, anyone?
I have been asked to give advice regarding the appropriateness of using
Scheme for a development effort in Intelligent Computer Assisted Instruction.
Although this is partly a research effort also, a clear goal is testing
and installing the software in high school classrooms. The hardware available
to this project is Hewlett-Packward workstations.
Admittedly I know little about Scheme. However, my initial reaction is that
no advantages Scheme could provide over CommonLisp could offset the
disadvantages of using a language without a large user base for the
purposes of software development and installation. CommonLisp
promises to offer portability (of course there are still problems, e.g.,
graphics) and a large user community, and has other obvious advantages
because of the general acceptance of Lisp in the U.S. AI community.
I'd appreciate some feedback from people that are familiar with Scheme,
particularly if you have used it for developing a large AI-based system.
Can any argument be presented to justify the resources necessary to train
people in Scheme and build and maintain a system in this UnCommonLispLike
language? In other words, what is so special about Scheme compared to
CommonLisp?
Mark
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Date: 10-Jun-1986 1436
From: cherubini%cookie.DEC@decwrl.DEC.COM
Subject: Neural Nets
I am interested in doing some modelling using neural nets. Before
building the software system myself, I would like to know of any
available public domain software systems which implement neural
nets, Boltzmann machines, etc. Any pointers would be appreciated.
Ralph Cherubini
Digital Equipment Corporation
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Date: 9 Jun 1986 1735-EDT
From: Bruce Krulwich <KRULWICH@C.CS.CMU.EDU>
Subject: connectionism/complexity theory
June 2nd's issue of Business Week contained an article about
connectionist (parallel distributed processing) models. In it it
mentioned a Bell Labs project which set up a neural network which solved
the traveling salesman problem aproximately but quickly. I'm interested
in articles or other information about this project or any other project
linking connectionism with complexity theory, ie, connectionist
approaches to graph problems or models which solve other "classical"
algorithm design problems.
Bruce Krulwich
ARPAnet: KRULWICH@C.CS.CMU.EDU
Bitnet: BK0A%TC.CC.CMU.EDU@CU20B
------------------------------
Date: Tue, 10 Jun 86 14:04 EST
From: MUKHOP%RCSJJ%gmr.com@CSNET-RELAY.ARPA
Subject: Creativity and Analogy
At a recent talk in Ann Arbor, Roger Schank observed/implied that
a distinct characteristic of many creative people is the ability to
analogize. My understanding of analogizing is to define transformations
between two domains so that entities and relationships in one domain
can be mapped into corresponding entities and relationships in the
other domain. It appears that the greater the disparity in the "physics"
of the two domains, the higher is the creative effort demanded.
Not all transformations produce interesting results. Good analogies
must be interesting from the perspective of the particular creative
activity.
Is this model of creativity--making interesting analogies--valid
across the spectrum of creative actvities, from the hard sciences
(Physics, Chemistry, etc.) to the fine arts (painting, music)?
Is there more to creativity than making interesting analogies? I am
inclined to believe that making interesting analogies is at the heart
of all intelligent activity that is described as creative.
Uttam Mukhopadhyay
General Motors Research Labs.
(313)575-2105
Net address: mukhop@gmr.com
------------------------------
Date: Tue 10 Jun 86 09:38:50-PDT
From: Mark Richer <RICHER@SUMEX-AIM.ARPA>
Subject: AI and Education questionnaire
Below is a questionnaire requesting information from researchers who are
interested in the application of Artificial Intelligence in education.
If you are working in this area or are interested in this area please look
at the questionnaire and fill it out. [...] You can also fill out
the questionnaire on-line and return it by email to the address provided
below.
This questionnaire is part of a larger effort to facilitate communication
among researchers in this area. We are also maintaining a list of postal
addresses of those people that are interested in joining a special interest
group in AI and education. One activity planned is a special interest group
meeting at AAAI '86 this August in Philadelphia. An annoucement of this
meeting will be forthcoming.
AI and Education Questionnaire
prepared 10 June 1986 by W. Lewis Johnson and Mark H. Richer
Please send your responses to:
W. Lewis Johnson
USC ISI
4676 Admiralty Way
Marina del Ray, CA 90292
or email to JOHNSON@ISI-VAXA.ARPA
(1) Name:
(2) Institution or Company:
(3) Street Address:
(4) City, State [or Country], Zip Code:
(5) Work Phone(s):
(6) E-Mail address(es):
(7) Are you interested in membership in an AI and Education group if one is
officially formed?
(8) What kind of organization(s) are you connected with? (Check one or more)
1. academic research laboratory
2. academic software development center
3. industrial or commercial research laboratory
4. commerical software company
5. educational institution (please explain)
6. government or military research & development
7. other (please specify)
(9) Please characterize your interest and involvement in AI and Education.
Please check one and elaborate.
1. I am currently building an AI-based instructional system. (Please
describe)
2. I am planning to build an AI-based instructional system. (Please
describe)
3. I'm not currently planning to build an instructional system, but I
want to keep abreast of developments in the field. (Why?)
4. I'm generally curious about the field. (Why?)
(10) Please list the subject areas that interest you (e.g., arithmetic, medical
diagnosis, auto mechanics, etc.).
(11) Is your work targeted to a specific student population? If so, please
indicate which.
1. pre-school or elemementary school students
2. junior high school or high school students
3. disabled or special students
4. college students
5. post-graduate or professional students
6. vocational trainees
7. military training
8. industrial training
9. other (please describe)
(12) Which do you consider to be among your MOST central interests?
1. authoring tools or environments (general architectures)
2. diagnosis of student errors and misconceptions
3. educational games
4. explanation and knowledge transfer techniques
5. designing curricula that uses AI-based systems
6. interactive video or CD-ROM
7. micro-worlds or learning environments
8. natural language
9. representation and codification of domain knowledge for the purpose
of instruction
10. representation and codification of general problem-solving knowledge
for the purpose of instruction
11. representation and codification of teaching knowledge for the
purpose of instruction
12. student modeling
13. tutorial strategies
14. user-interfaces (including use of computer graphics in general)
15. user-modeling (for explanation, on-line contextual help, user-
interfaces)
16. voice recognition/synthesis
17. other (please specify)
(13) Which of the following would you like to see a special interest group in
AI and Education offer? (0=not important, 1=important, 2=very important)
1. electronic discussion list
2. bibliographic references without abstracts/reviews
3. bibligraphic references with abstracts/reviews
4. annual meeting at AAAI
5. periodic focused workshops
6. high quality feedback on paper drafts, proposals, ideas, etc.
7. job announcements
8. other:
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End of AIList Digest
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