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AIList Digest Volume 2 Issue 049
AIList Digest Friday, 20 Apr 1984 Volume 2 : Issue 49
Today's Topics:
AI Programming - Cfasling Pascal routines into Franz,
AI Tools - Prolog on Symbolics Machines,
Expert Systems - Real-Time Simulation,
Jobs - Noncompetition Agreements,
AI Programming - Discussion,
Linguistics - Use of "and",
Seminar - Puzzles and Permutation Groups,
Conference - Expert Database Systems Workshop
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Date: 12 Apr 1984 07:52:11-EST
From: Nasa.Langley.Research.Center@CMU-RI-ROVER
Subject: Cfasling Pascal routines into Franz
In our work with distributed intelligent systems for space teleoperators
and robotics, we have found the "cfasl" function in Franz Lisp to be very
useful, connecting previously-developed Fortran routines to the total
system. However, a need has arisen to use an external Pascal function,
and we have been unable to persuade Franz to accept this in our system.
We have even tried to front-end Pascal modules with Fortran in order to
cfasl, but can't even manage that. Any suggestions from someone who has
done this? We are running Franz opus 38.17 on a *VAX/VMS* 750, not Unix.
We do have the Eunice system.
The heart of the problem is that
I'm using VAX/VMS Pascal, not the Unix/Eunice pascal. Evidently the VMS
pascal is not generating global symbols in a way that is visible to the
cfasling functions. In fact, I haven't gotten it to be visible to the linker
in VMS calling pascal modules from other languages, say fortran. Probably
if I could get that, I could get the other.
Mailing address is:
Nancy Orlando
Mail Stop 152D
NASA Langley Research Center
Hampton, VA 23665
Thanks in advance...
Nancy Orlando
------------------------------
Date: Mon 16 Apr 84 16:56:05-CST
From: Oliver Gajek <LRC.Gajek@UTEXAS-20.ARPA>
Subject: Prolog on Symbolics machines
Does anyone know whether there is a PROLOG available for a Symbolics
Lisp machine? If so, can you run it simultaneously with Lisp and call
it from there? And how does it compare to other implementations?
Thanks,
Oliver.
------------------------------
Date: 17 Apr 1984 21:27:06 EST
From: Perry W. Thorndyke <THORNDYKE@USC-ISI>
Subject: Real-Time Simulation
Response to request for information on AI-based real-time simulation:
We at Perceptronics are developing a real-time simulation of a Navy
tactical decision-making environment for use in an instructional system.
The environment simulates an air-sea battle situation in which the student
must command a ship, utilizing sensors, weapons, maneuvering, and deception
to defend himself against an opposing ship(s). The battle simulation and
opponent simulation must run in real time to present a realistic training
situation. From an instructional perspective, the interesting research
issues involve (1) how to represent the skills associated with real-time
cognition on a time-stressed problem, and (2) how to make the opponent
simulation modifiable under program control by the instructional system
so that exercises can address particular pedagogical objectives. We are
currently working in GLISP, which sits on top of Franz Lisp on a VAX.
We utilize 4 mb of main memory.
Perry Thorndyke
Perceptronics Knowledge Systems Branch
thorndyke@usc-isi
------------------------------
Date: 17 Apr 1984 21:59:32 EST
From: Perry W. Thorndyke <THORNDYKE@USC-ISI>
Subject: Noncompetition
Response to Fahlman's message on noncompetition clauses:
Scott,
We continually hire AI talent into our for-profit, public company to
conduct R&D on expert systems, surrogate instructors, intelligent human-
machine interfaces, and distributed AI. Several of our products contain
proprietary hardware-software designs and our market advantage depends
on maintaining a technology edge in those product areas, which include
videodic/graphics display systems. Yet we have no such noncompetition
clause, nor have we considered imposing one. Given that it is a
seller's market for AI talent now, it's hard to believe that any company
could get away with imposing such a policy--assuming that it is even
legally enforcable. My experience in the AI field is that conflict-of-
interest considerations do not extend beyond the term of employment
of the individual, except for non-disclosure of proprietary information.
The policy you cited seems extreme and undesirable, and constitutes
a moral, if not legal, unfair restraint of trade.
Perry Thorndyke
Perceptronics, Inc.
thorndyke@usc-isi
------------------------------
Date: Wed 18 Apr 84 11:22:44-PST
From: WYLAND@SRI-KL.ARPA
Subject: Stolfo's call for discussion
Your question - "What are the fundamental characteristics
of AI computation that distinguish it from more conventional
computation." - is a good one. It is answered, consciously or
unconsciously, by each of us as we organize our understanding of
the field. My own answer is as follows:
The fundamental difference between conventional programs
and AI programs is that conventional programs are static in
concept and AI programs are adaptaive in concept. Conventional
programs, once installed, have fixed functions: they do not
change with time. AI programs are adaptive: their functions and
performance improve with time.
A conventional program - such as a payroll program, word
processor, etc. - is conceived of as a static machine with a
fixed set of functions, like a washing machine. A payroll
program is a kind of "cam" that converts the computer into a
specific accounting machine. The punched cards containing the
week's payroll data are fed into one side of the machine, and
checks and reports come out the other side, week after week. In
this concept, the program is designed in the same manner as any
other machine: it is specified, designed, built, tested, and
installed. Periodic engineering changes may be made, but in the
same manner as any other machine: primarily to correct problems.
AI programs are adaptive: the program is not a machine
with a fixed set of functions, but an adaptive system that grows
in performance and functionality. This focus of AI can be seen
by examining the topics covered in a typical AI text, such as
"Artificial Intellegence" by Elaine Rich, McGraw-Hill, 1983.
The topics include:
o Problem solving: programs that solve problems.
o Game playing
o Knowledge representation and manipulation
o Natural language understanding
o Perception
o Learning
These topics are concerned with adaptation, learning, or
any of several names for the same general concept. This seems to
be the consistant characteristic of AI programs. The interesting
AI program is one that can improves its performance - at solving
problems, playing games, absorbing and responding to questions
about knowledge, etc. - or one that addresses issues associated
with problem solving, learning, etc.
The adaptive aspect of AI programs implies some
difference in methods used in the programs. AI programs are
designed for change, both by themselves while running, and by the
original programmer. As the program runs, knowledge structures
may expand and change in a number of dimensions, and the
algorithms that manipulate them may also expand - and change
THEIR structures. The program must be designed to accommodate
this change. This is one of the reasons that LISP is popular in
AI work: EVERYTHING is dynamically allocated and modifyable -
data structures, data types, algorithms, etc.
Good luck in your endeavors! It is a great field!
Dave Wyland
WYLAND@SRI
------------------------------
Date: 12 Apr 84 15:51:48-PST (Thu)
From: harpo!ulysses!burl!clyde!akgua!psuvax!burdvax!sjuvax!bbanerje @
Ucb-Vax
Subject: Re: Use of "and"
Article-I.D.: sjuvax.254
>> There is another way of looking at the statement -
>> all customers in Indiana and Ohio
>> which seems simpler to me than producing the new phrase -
>> all customers in Indiana AND all customers in Ohio
>> instead of doing this why not treat Indiana and Ohio as a new single
>> conceptual entity giving -
>> all customers in (Indiana and Ohio).
>>
>> This seems simpler to me. It would mean the database would have to
>> allow aggregations of this type, but I don't see that as being
>> particularly problematic.
>>
>> Jim Cowie.
My admittedly inconsequential contribution to this:
(Pardon the Notation! Here, Indiana and Ohio correspond to sets
of base type customer. C- denotes set membership and (~) is
intended to denote set intersection.)
All customers in Indiana AND all customers in Ohio seems to want the
following :
[all customers such that |
{customer C- Indiana} XOR {customer C- Ohio}]
This seems to be described best as
[all customers such that |
customer C- {Indiana U Ohio - (Indiana (~) Ohio)}]
Assuming that no customer can be in Indiana and Ohio simultaneously,
the intersection of the sets would be NULL. Thus we would have
[all customers such that |
customer C- {Indiana U Ohio}]
So far so good. However, the normal sense of an AND as I understand
it, corresponds to a set intersection. The formulation is therefore
counter-intutive.
I'm not an AI type, so I would appreciate being set straight. Flames
will be cheerfully ignored.
Regards,
Binayak Banerjee
{allegra | astrovax | bpa | burdvax}!sjuvax!bbanerje
------------------------------
Date: 18 April 1984 15:27-EST
From: Kenneth Byrd Story <STORY @ MIT-MC>
Subject: puzzles and permutation groups
[Forwarded from the MIT bboard by Laws@SRI-AI.]
DATE: Thursday, April 19, 1984
TIME: Lecture, 4:00pm
PLACE: NE43-512a
``Generalized `15-puzzles' and the Diameter of Permutation Groups''
Dan Kornhauser
MIT
Sam Lloyd's famous ``15-puzzle'' involves 15 numbered unit squares free to move
in a 4x4 area with one unit square blank. The problem is to decide whether a
given rearrangement of the squares is possible, and to find the shortest
sequence of moves to obtain the rearrangement when it is possible.
A natural generalization of this puzzle involves a graph with @i(n) vertices,
and @i(k<n) tokens numbered @i(1,...,k) on distinct vertices. A legal move
consists of sliding a token from its vertex to an adjacent unoccupied vertex.
Wilson (1974) obtained a criterion for solvability for biconnected graphs and
@i(k=n-1). No polynomial upper bound on number of moves was given.
We present a quadratic time algorithm for deciding solvability of the general
graph problem. It is also shown that @i[O(n@+{3})] move solutions always exist
and can be efficiently planned. Further, @i[O(n@+{3})] is shown to be a
matching lower bound for some graph puzzles.
We consider related puzzles of the Rubik's cube type, in the context of the
general permutation group diameter question.
This is joint work with Gary Miller, MIT, and Paul Spirakis, NYU
HOST: Professor Silvio Micali
------------------------------
Date: 12 Apr 84 12:31:31-PST (Thu)
From: harpo!ulysses!allegra!carlo @ Ucb-Vax
Subject: Expert Database Systems Workshop (long msg)
Article-I.D.: allegra.2406
Call for Papers and Participation
FIRST INTERNATIONAL WORKSHOP ON EXPERT DATABASE SYSTEMS
October 25-27, 1984, Kiawah Island, South Carolina
Sponsored by
The Institute of Information Management, Technology, and Policy,
College of Business Administration,
University of South Carolina
In Cooperation With
Association for Computing Machinery - SIGMOD and SIGART
IEEE Technical Committee on Data Base Engineering
Workshop Program
This workshop will address the theoretical and practical issues
involved in making databases more knowledgeable and supportive of AI
applications. The tools and techniques of database management are
being used to represent and manage more complex types of data and
applications environments.
The rapid growth of online systems containing text, bibliographic, and
videotex databases with their specialized knowledge, and the develop-
ment of expert systems for scientific, engineering and business appli-
cations indicate the need for intelligent database interfaces and new
database system architectures.
The workshop will bring together researchers and practitioners from
academia and industry to discuss these issues in Plenary Sessions and
specialized Working Groups. The Program Committee will invite 40 to
80 people, based on submitted research and application papers (5000
words) and issue-oriented position papers (2000-3000 words).
Topics of Interest
The Program Committee invites papers addressing (but not limited to)
the following areas:
Knowledge Base Systems Knowledge Engineering
environments acquisition
architectures representation
languages design
hardware learning
Database Specification Methodologies Constraint and Rule Management
object-oriented models metadata management
temporal logic data dictionaries
enterprise models constraint specification
transactional databases verification, and enforcement
Reasoning on Large Databases Expert Database Systems
fuzzy reasoning natural language access
deductive databases domain experts
semantic query optimization database design tools
knowledge gateways
industrial applications
Please send five (5) copies of full papers or position papers by June
1, 1984 to:
Larry Kerschberg, Program Chairperson
College of Business Administration
University of South Carolina
Columbia, SC, 29208
(803) 777-7159 / (803) 777-5766 (messages)
USENET: ucbvax!allegra!usceast!kersch
CSNET: kersch@scarolina
Submissions will be considered by the Program Committee:
Bruce Berra, Syracuse University Sham Navathe, Univ. of Florida
James Bezdek, Univ. of South Carolina Erich Neuhold, Hewlett-Packard
Michael Brodie, Computer Corp. of America Stott Parker, UCLA
Janis Bubenko, Univ. of Stockholm Michael Stonebraker, UC-Berkeley
Peter Buneman, Univ. of Pennsylvania Yannis Vassiliou, New York Univ.
Antonio L. Furtado, PUC-Rio de Janeiro Adrian Walker, IBM Research Lab.
Jonathan King, Symantec Bonnie L. Webber, U. of Penn.
John L. McCarthy, Lawrence Berkeley Lab. Gio Wiederhold, Stanford Univ.
John Mylopoulos, University of Toronto Carlo Zaniolo, AT&T Bell Labs
Authors will be notified of acceptance or rejection by July 16, 1984.
Preprints of accepted papers will be available at the workshop.
Workshop presentations, discussions, and working group reports will be
published in book form.
Workshop General Chairman Local Arrangements Chairperson
Donald A. Marchand Cathie Hughes-Johnson
Institute of Information Management, Technology and Policy
(803) 777-5766
Working Group Coordinator Industrial Liaison
Sham Navathe Mas Tsuchiya
Computer and Information Sciences TRW 119/1842
University of Florida One Space Park Drive
512 Weil Hall Redondo Beach, CA 90278
Gainesville, FL 32611 (213) 217-6114
(904) 392-7442
_________________________________________________________________________
Response Card (Please mail to address on below)
Name ___________________________________________ Telephone _____________
Organization ___________________________________________________________
Address ________________________________________________________________
City, State,
ZIP, and Country ________________________________________________________
Please check all that apply:
_____ I intend to submit a research paper.
_____ I intend to submit an issue-oriented position paper.
_____ I would like to participate in a working group.
General Topic Areas _________________________________________
_____ Not sure I can participate, but please keep me informed.
Subject of paper ______________________________________________________
_______________________________________________________________________
Cathie Hughes-Johnson
Institute of Information Management
Technology and Policy
College of Business Administration
University of South Carolina
Columbia, SC 29208
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End of AIList Digest
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