Copy Link
Add to Bookmark
Report
AIList Digest Volume 6 Issue 019
AIList Digest Friday, 29 Jan 1988 Volume 6 : Issue 19
Today's Topics:
Queries - Neural Net Study Group & Edinburgh TRs &
Knowledge Acquisition References & Ten Best Vision References &
Comparative Language Structures & Engineering Data Modelling &
XLISP 1.5 & Testing and Evaluating an Expert System &
AI in Management,
Application - Table Tennis-Playing Robot,
AI Tools - PROLOG for an IBM 3090 under CMS &
Software Development and Expert Systems &
IXL Machine Learning System
----------------------------------------------------------------------
Date: 25 Jan 88 13:43:30 PST (Monday)
From: Rockwell.HENR801c@Xerox.COM
Reply-to: Rockwell.HENR801c@Xerox.COM
Subject: Neural Net Study Group
I'm trying to find members of Xerox in Rochester,NY interested in
joinning/forming a neural net/connectionist study group. Interested parties
should reply to ROCKWELL:HENR801C:XEROX.
------------------------------
Date: 26 Jan 88 21:22:37 GMT
From: rao@cvl.umd.edu (Subbarao Kambhampati)
Subject: Request for an Edinburgh TR (Austin Tate, Non-Lin)
I am trying to get hold of the following two technical reports.
I would appreciate it very much if anyone who has them can send me copies.
I could write to Edinburgh, but I need them fast and thought this request
may bear quicker results..
The TRs:
Austin Tate, Project planning using a Hierarchic Non-linear Planner,
Research Report 245, Dept of AI, Univ of Edinburgh, 1976
Austin Tate, Using Goal sturcture to direct search in a problem
solver, Department of AI, University of Edinburgh, 1975.
I am particularly interested in the former.
My USMail address is:
Subbarao Kambhampati
GRA, Center for Automation Research
University of Maryland
College Park, MD 20742
Thanks in anticipation
-rao
------------------------------
Date: 25 Jan 88 08:51:16 GMT
From: fordjm@byuvax.bitnet
Subject: Knowledge Acquisition References (Request)
I am interested in knowledge elicitation issues and have run across
several references to the following papers:
Welbank, M. (1983). A review of knowledge acquisition techniques
for expert systems. Martelsham Consultancy Services, Ipswich, UK.
and
Wielinga, B. J. & Brueker, J. A. (1984). Interpretation of verbal
data for knowledge acquisition. Proceedings of ECAI-84, Pisa, Italy,
pp. 41-50.
Does anyone know where I can obtain these papers?
Thanks in advance,
John M. Ford fordjm@byuvax.bitnet
131 Starcrest Drive
Orem, UT 84058
------------------------------
Date: 28 Jan 88 00:15:09 GMT
From: hunt@spar.SPAR.SLB.COM (Neil Hunt)
Reply-to: hunt@spar.UUCP (Neil Hunt)
Subject: Ten best vision references..
I would like to collect votes for the ten most important references
in the field of computer vision. I will compile a list and repost
if there is sufficient response. Feel free to vote for one paper,
or as many as you like; each mention by a separate person
counts as one vote.
Neil/.
...{amdahl|decwrl|hplabs}!spar!hunt hunt@spar.slb.com
------------------------------
Date: Wed, 20 Jan 88 15:19:48 MST
From: yorick%nmsu.csnet@RELAY.CS.NET
Subject: Query - Comparative Natural/Formal Language Structures
Appeal for references/pointers to a possible literature on
comparative structures of natural and formal languages.
We propose to investigate the possible relationship between (1)
the minimum structures of natural language, and (2) the minimum
structures of programming languages, and seek help in the form
of references to work already done.
There are two ways to approach the minimum structures necessary
to a natural language -- formal and empirical.
The formal structure of natural languages is still under debate,
and that debate is easily found in grammar studies.
As for the empirical, lists of phenomena common to all known
natural languages are known, such as NP's, VP's, direct objects,
interrogation, negation, and sentences. What are the standard, and
even non-standard, references for such lists?
Lastly, is there existing work on the relationship itself? Has anyone
compared:
a) subject and predicate to data and control structures, or
b) declarative, imperative, and interrogative utterances, to types of
accesses to a variable (declaration, definition, and reference), or
c) phonemes, morphemes, and comprehension in speaking, to tokens, objects, and
compilation in programming?
Thank you for any suggestions or references, even those which seem obvious.
Please reply to rhill@nmsu.csnet
------------------------------
Date: Wed, 27 Jan 1988 23:50:12 EST
From: Deeptendu Majumder
Subject: Engineering Data Modelling Info
I am working in the area of Engineering Databases, here at Georgia
Tech, and looking for information on Enginnering Data Modeling.
Can anybody provide me with a list of good references in this area.
Information on software packages for data modeling and names and
address of people actively involved in this area will be also very
helpful. The stress is on Engineering Data. I would really
appreciate any help.
Thanx in advance
Deeptendu Majumder
MEIBMDM@GITVM2
Box 30963
Georgia Tech
Atlanta, GA 30332
------------------------------
Date: Thu, 28 Jan 88 12:33:11 EST
From: Bill Delaney <WPD@IRISHVM.BITNET>
Reply-to: AIList@Stripe.SRI.COM
Subject: Query - XLISP 1.5
Does anyone out there know where I can find a copy of XLISP version 1.5?
Thanks in advance.
------------------------------
Date: Thu, 28 Jan 88 16:09:57 PST
From: lambert@cod.nosc.mil (David R. Lambert)
Subject: Procedures for Testing & Evaluating an Expert System
Ken-- Please post this in the next issue of AIList. There was a similar
request in a recent issue, but since I have a specific deadline, I'd
appreciate the additional posting. Thanks. --Dave
---------------
I need information on how to test and evaluate an expert system. I have seen
the Feb 88 AI-Expert article, and would greatly appreciate additional relevant
information which I can obtain by Feb 10.
lambert@nosc.mil
David R. Lambert
Naval Ocean Systems Center
San Diego, CA 92152
(619) 553-1093
------------------------------
Date: Fri, 29 Jan 88 10:30:03 SST
From: Joel Loo <ISSLPL%NUSVM.BITNET@CUNYVM.CUNY.EDU>
Subject: Query: AI works in Management
I am posting this for a colleague: (Please reply to ISSAD@NUSVM.BITNET)
There aren't many AI research works on Management that I've
come across. I hope to get to know those who are doing
research to apply AI in the various disciplines of Management.
------------------------------
Date: Mon, 25 Jan 88 08:58:19 PST
From: Stephen Smoliar <smoliar@vaxa.isi.edu>
Subject: Re: table tennis playing robot
Since I was at the MIT Artificial Intelligence Laboratory during the 60's,
I can flesh out some of Rob Elkins comments. When I first arrived, there
was a major effort to build a robot which could play table tennis. (I think
this was the summer of 1966.) There was an "arm" which was an AMF manipulator
which operated in cylindrical coordinates and a simple vidicon "eye." When
I arrived, a basket had been attached to the end of the arm, and development
was concerned with getting the arm to catch the ball based on the trajectory
tracked by the eye. Because of the relatively primitive environment, there
were all sorts of problems. For example, the initial version really didn't
work in three dimensions. Thus, for a successful test, one had to throw
the ball in a specific plane; and the arm could only adjust itself on
the up-down and forward-back axes. As I recall, there was a joke to the
effect that, after six months of intensive development of both hardware and
software (the MIDAS assembled on a PDP-6), all researchers had learned how
to throw the ball in such a way that the arm didn't have to move!
I was not there when the arm tried to catch Marvin Minksy's (bald) head.
So I don't know if the story is really true. Given the intricacies of
setting up a test, I suspect it is at least a slight exaggeration.
Attention subsequently shifted to an arm with four (I think) hydraulically
controlled flex-extend joint. However, I do not think this arm ever caught
any flying objects. (As a matter of fact, I'm not sure it was ever
controlled effectively for any purpose.)
------------------------------
Date: 28 Jan 88 00:55:40 GMT
From: munnari!augean.oz.au!pfranzon@uunet.UU.NET (Paul Franzon)
Reply-to: pfranzon%augean.OZ@uunet.UU.NET (Paul Franzon)
Subject: Re: table tennis playing robot
>I believe the table tennis playing robot work was done by Bell Labs at
>one of their New Jersey locations (probably Murray Hill or Holmdel).
Yes:
Robotic Systems Research Dept.,
AT&T Bell Labs
Holmdel NJ 07733
Head: John Jarvis, room 4B-601 (e-mail: jfj@vax135)
------------------------------
Date: Tue, 26 Jan 88 21:34:07 EST
From: humphrey@mcs.nlm.nih.gov (Susanne M. HUMPHREY)
Subject: robot ping-pong player in Philadelphia
Among the dissertation abstracts in a forthcoming edition of AI-Related
Dissertations in SIGART Newsletter:
AN University Microfilms Order Number ADG87-14001.
AU ANDERSSON, RUSSELL LENNART.
IN University of Pennsylvania Ph.D 1987, 339 pages.
TI REAL TIME EXPERT SYSTEM TO CONTROL A ROBOT PING-PONG PLAYER.
SO DAI v48(05), SecB, pp1412.
DE Computer Science.
AB A real time "expert" control system has been designed and forms
the nucleus of functioning robot ping-pong player.
Robot ping-pong is underconstrained in the task specification (hit
the ball back), and heavily constrained by the manipulator
capabilities. The expert system must integrate the sensor data,
robot capabilities, and task constraints to generate an acceptable
plan of action. The robot ping-pong task demands that the planner
anticipate environmental changes occurring during planning and
robot motion. The inability to generate accurate, timely plans
even in the face of a capricious environment and limited actuator
performance would result in a nonfunctional system.
The program must continuously update the task plan as new sensor
data arrives, selecting appropriate modifications to the existing
plan, rather than treating each datum independently. The difficult
task and the stream of sensor data result in an interesting system
architecture. The expert system operates in the symbolic and
numeric domains, with a blackboard to enable global optimization
by local agents. The architecture interrelates initial planning,
temporal updating, and exception handling for robustness.
A sensor and processing system produces three dimensional
position, velocity, and spin vectors plus a time coordinate at 60
Hz. Novel processing algorithms and careful attention to camera
modeling were necessary to obtain adequate accuracy.
A robot controller provides accurate, predictable performance
close to the envelope of robot capabilities using modeling and
feed-forward techniques. The controller plans motions in the
temporal domain including specified terminal velocities, and
supports smooth changes to motions in progress.
The performance of the sensor subsystem, actuator and robot
controller, and expert system have been demonstrated. The system
successfully plays against both human and machine opponents.
------------------------------
Date: 26 Jan 88 02:03:38 GMT
From: quintus!jbeard@sun.com (Jeff Beard)
Subject: Re: PROLOG for an IBM 3090 under CMS
as of the fall of '87, Quintus Prolog was delivered as a runtime
library for the MVS/{SP,XA} and VM/370 Rel 4 environments.
This is system independant runtime support such that the compiler
*.text decks from one environment DO NOT require re-compilation
to support the other (given total absence of system dependant
file names).
The product is a cross-compiler, with the Prolog sources existing on
a Sun work-station and the generated objects uploaded and link-edited
with the runtime library supplied.
Contact Don Hester 415-965-7700
or
mail to
Quintus Computer Systems
1310 Villa Street
Mountain View, CA 94041
------------------------------
Date: Tue, 26 Jan 88 19:04:24 EST
From: jacob@nrl-css.arpa (Rob Jacob)
Subject: Re: Software Development and Expert Systems
To: sross@cs.ucl.ac.uk
Saw your message about software engineering techniques for expert
systems on the AIList. This may not be quite what you had in mind,
but, here at the Naval Research Laboratory Judy Froscher and I have
been working on developing a software engineering method for expert
systems. We are interested in how rule-based systems can be built so
that they will be easier to change. Our basic solution is to divide
the set of rules up into pieces and limit the connectivity of the
pieces.
I'm going to attach a short abstract about our work to the end of this
message and some references. Hope it's of use to you.
Good luck,
Rob Jacob
ARPA: jacob@nrl-css.arpa
UUCP: ...!decvax!nrl-css!jacob
SNAIL: Code 5530, Naval Research Lab, Washington, D.C. 20375
Developing a Software Engineering Methodology for Rule-based Systems
Robert J.K. Jacob
Judith N. Froscher
Naval Research Laboratory
Washington, D.C.
Current expert systems are typically difficult to change once they are
built. The objective of this research is to develop a design
methodology that will make a knowledge-based system easier to change,
particularly by people other than its original developer. The basic
approach for solving this problem is to divide the information in a
knowledge base and attempt to reduce the amount of information that
each single programmer must understand before he can make a change to
the expert system. We thus divide the domain knowledge in an expert
system into groups and then attempt to limit carefully and specify
formally the flow of information between these groups, in order to
localize the effects of typical changes within the groups.
By studying the connectivity of rules and facts in several typical
rule-based expert systems, we found that they seem to have a latent
structure, which can be used to support this approach. We have
developed a methodology based on dividing the rules into groups and
concentrating attention on those facts that carry information between
rules in different groups. We have also developed algorithms for
grouping the rules automatically and measures for coupling and cohesion
of alternate rule groupings in a knowledge base. In contrast to the
homogeneous way in which the facts of a rule-based system are usually
viewed, the new method distinguishes certain facts as more important
than others with regard to future modifications of the rules.
REFERENCES
R.J.K. Jacob and J.N. Froscher, "Facilitating Change in Rule-based
Systems," pp. 251-286 in Expert Systems: The User Interface, ed. J.A.
Hendler, Ablex Publishing Co., Norwood, N.J. (1988).
R.J.K. Jacob and J.N. Froscher, "Software Engineering for Rule-based
Systems," Proc. Fall Joint Computer Conference pp. 185-189, Dallas,
Tex. (1986).
J.N. Froscher and R.J.K. Jacob, "Designing Expert Systems for Ease of
Change," Proc. IEEE Symposium on Expert Systems in Government pp.
246-251, Washington, D.C. (1985).
R.J.K. Jacob and J.N. Froscher, "Developing a Software Engineering
Methodology for Rule-based Systems," Proc. 1985 Conference on
Intelligent Systems and Machines pp. 179-183, Oakland University
(1985).
R.J.K. Jacob and J.N. Froscher, "Developing a Software Engineering
Methodology for Knowledge-based Systems," NRL Report 9019, Naval
Research Laboratory, Washington, D.C. (1987).
------------------------------
Date: 27 Jan 88 20:36:05 GMT
From: harvard!bunny!harvard!bunny!gps0.UUCP@seismo.css.gov (Gregory
Piatetsky-Shapiro)
Reply-to: harvard!bunny!gps0.UUCP@seismo.css.gov (Gregory
Piatetsky-Shapiro)
Subject: Re: IXL - A Machine Learning System
IXL is a product of IntelligenceWare Corp, 9800 S. Sepulveda Blvd,
Suite 730, Los Angeles, CA 90045. They also make Intelligence/Compiler.
Call (213) 417 8896 for information.
These products run on an IBM PC. IXL is a very interesting product that
takes a database (ASCII, 1-2-3, dbase formats) and derives rules of the
form (if A > a and B between b1 & b2, then C = c with confidence XX).
Their product was advertised in AI Expert, IEEE Expert and AI Magazine.
I would be interested to see any experiences with IXL, and whether it
can derive some actually useful rules.
Gregory Piatetsky-Shapiro
Include <standard funny disclaimer>
--
Gregory Piatetsky-Shapiro gps0@gte-labs.relay.cs.net
GTE Laboratories, (617) 466-4236
40 Sylvan Road, Waltham MA 02254
************ A standard humorous disclaimer *************
------------------------------
End of AIList Digest
********************
