LAWS@SRI-AI.ARPA (11/16/84)
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-AI>
AIList Digest Friday, 9 Nov 1984 Volume 2 : Issue 151
Today's Topics:
AI Hardware - Fujitsu Facom Alpha
AI Literature - Journal of Intelligent Systems
& Artificial Intelligence Markets & Machine Intelligence News Digest,
Algorithms - Taxonomy and Uses of Malgorithms,
Program Description - Social Impacts of Computing, UC-Irvine
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Date: Fri, 9 Nov 1984 13:20 EST
From: Chunka Mui <CHUNKA%MIT-OZ@MIT-MC.ARPA>
Subject: AI Hardware - Fujitsu Facom Alpha
In a recent issue of Electronic News (I think it was October), there
was an article on AI systems which was interesting. After the usual
discussion about Symbolics, LMI, and Xerox lisp machines, the article
discussed a Fujitsu machine called the "facom alpha" which was priced
at 90K and which Gary Moskovitz of Xerox described as a "back-end
processor to a main frame." Now it doesn't seem that 90K for a
back-end processor is much of a bargain, but I think the idea of a
very fast Lisp processing back end for a mainframe is worth looking
at. To be able to use a 3600 or a Lambda as a development environment
but know that one could ultimately use a mainframe as the execution
environment would, I think, make big business look more kindly upon
potential AI projects.
Has anyone out there seen the Fujitsu machine or know anything about
it? I like to hear whatever information, thoughts, rumors, etc.
people had on it. If there is a Fujitsu person out there, I'd be
interested in hearing from you.
I'd also like to know what kind of thoughts people had on this topic:
lisp back ends for mainframes that can roughly compare with the
various lisp machines as oppose to single user work station that are
used now. Is anyone working on such a thing here in the U.S.?
Thanks,
Chunka Mui
Chunka%mit-oz@mit-mc
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Date: Mon 5 Nov 84 14:53:19-PST
From: C.S./Math Library <LIBRARY@SU-SCORE.ARPA>
Subject: Journal of Intelligent Systems
[Forwarded from the Stanford bboard by Laws@SRI-AI.]
I have received very brief information on a journal to appear in 1985.
The Journal of Intelligent Systems will be published by Freund Publishing
House Ltd., London England for $120 per year, a quarterly. The editors
are Frank George, Les Johnson, and Mike Wright of Brunel University,
Uxbridge England. The managing editor is Mrs. Alison Lovejoy, AA
publishing Services, London England. The Aims and Scopes are described
as follows:
...to provide research and review papers on an interdisciplinary level, where
the focal point is the field of intelligent systems. This field includes:
the empirical study and modelling of natural intelligent systems (human
beings and also relevant studies in evolutionary theory and biology);
the theoretical analysis of possible systems which could display intelligence,
the development and enhancement of intelligent systems (eg learning theories)
the designing of intelligent systems (or the application of intelligent systems
concepts to the design of semi-intelligent machines) and the philosophical
aspects of the field of intelligent systems.
It is believed that technological advances in such areas as robotics and
knowledge based systems are facilitated by interdisciplinary communcication.
Additionally, those sciences which are concerned with the understanding of
human intelligence stand to gain by such a dialogue.
In keeping with the interdisciplinary intent of the journal, papers will be
written for general professional readership. It is therefore important
that technical jargon should be avoided, or it used , shld be made
explicit...........
An editorial board of 20 is being formed at present. If anyone has any
information or opinions about this publication, please let me know.
Does it sound like something I should order for the Math/CS Library?
Harry Llull
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Date: Wed 7 Nov 84 11:24:31-PST
From: Ken Laws <Laws@SRI-AI.ARPA>
Subject: Artificial Intelligence Markets
I just got a flier from AIM Publications, P.O. Box 156, Natick, MA 01760.
They are planning a newsletter, Artificial Intelligence Markets, to
track the AI business world starting in January 1985. The price is
$255 regular, $195 charter, $380 2-year, and $550 3-year for 12 issues
per year of eight pages each.
The flier claims this to be the ONLY publication dedicated to covering
commercial AI (also DoD and Fifth Generation coverage). Perhaps they
aren't aware of the AI Report from AI Publications (95 first st., Los
Altos, CA 94022), or of the Georgia Tech (?) newsletter described in
AIList about six months ago. I've also heard recently of an "AI and
its Applications" newsletter, but have no details.
The flier does mention levels of AI investment by U.S. companies, and
claims that the current AI market of $125 million (36% software, 12%
intelligent robots, 52% LISP workstations) will expand to $4,440 million
by 1990: 43% software (7% LISP, 13% expert system tools, 5% natural
language, 8% programming languages, 8% military, 2% other), 15%
intelligent robots, 28% LISP workstations, 11% other processors, and
3% AI communications.
-- Ken Laws
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Date: Wed 7 Nov 84 15:32:24-PST
From: Ken Laws <Laws@SRI-AI.ARPA>
Reply-to: AIList-Request@SRI-AI
Subject: Machine Intelligence News Digest
From the November issue of IEEE Spectrum, p. 123:
Yet another newsletter covering the field of artificial intelligence
has been announced, but this time it comes from the United Kingdom.
Machine Intelligence News Digest is the first British news publication
to monitor artificial intelligence on a monthly basis. It will
concentrate on the existing and potential applications of AI and
their impact on the industrial and commercial world. It will also
include a calendar of events and a publication review section.
Regular coverage will be given to artificial vision and speech
recognition, AI languages such as LISP, integrating intelligent
machines with computer-aided systems, and AI research programs.
These include the DARPA effort in the United States, the fifth-
generation project in Japan, and the Esprit program in France.
The monthly newsletter costs 110 pounds annually ($140). Subscription
information is available by writing the publisher, Oyez Scientific
and Technical Services Ltd., Bath House, 3rd Fl., 56 Holborn Viaduct,
London EC1A 2EX, England; or calling 01-236-4080.
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Date: 7 Nov 84 14:06:29 EST
From: BIESEL@RUTGERS.ARPA
Subject: Taxonomy of malgorithms.
Now that the concept of malgorithms has been defined it behooves us as
serious scientists to classify the different kinds of malgorithms, to
write learned papers in obscure journals, and to generally do everything
to bring scholarly respectability to this heretofore underrecognized area
of computer science. The following is a modest contribution to the
establishment of a taxonomy of malgorithms.
The notion of an optimal algorithm is an old one, and the definition of
of optimality in time, say, or in storage is straightforward. The little
"o" and the big "O" notation is well established and suffices to define
the complexity of an algorithm (except for a constant or two), and thus
permits the comparison of two algorithms for the same problem. The optimal
algorithm is therefore simply that algorithm which has the lowest
time complexity for any given problem. Often it is possible to prove
mathematically that the best possible algorithm for a given class of problems
cannot do better than some lower bound.
The converse of this, the worst possible algorithm, is not as easily defined.
Is the worst possible algorithm one that never finishes, while wiping
out every piece of storage and tying up your computer until you unplug
it? Or, more insidious, does this algorithm appear to run normally,
generate recognizable output, but produce results that are subtly wrong,
so wrong as to cause maximum damage when the results are used?
If we restrict our considerations only to those algorithms that
actually produce the correct result, but do so in the longest possible
time, we run into other problems. The concept of 'longest possible time'
is ill-defined, since we do not know the temporal extent of the
universe. Neglecting for the moment the relatively trivial problem
of how to keep a computer running forever ( a hardware problem, and
therefore not worthy of our consideration), we still need to
define some upper bounds on the time intervals we are considering.
Assumption 1: The universe will exist forever.
Definition 1: Any algorithm that runs forever before it produces the
correct result is a member of the class "Aleph Zero". Extensions
to algorithms that take longer than this are made in the obvious way
(i.e. classes aleph one etc.). The development of such an algorithm
is left as an exercise to the reader.
Assumption 2: The universe will exist until some terminal
climactic event.
Definition 2: Any algorithm that runs a finite amount of time,
and produces its output at the last moment of existence, is a
member of the class "Gabriel". (members of non-christian
religions may wish to substitute a climactic event of their own
choice).
While the classes thus far defined would appear to specify
theoretical upper bounds for malgorithm execution times, some
practitioners may be concerned with malgorithms that take into
account the limitations of present hardware configurations. While
this kind of pandering to mechanical strictures is abhorrent
to every theoretician, some precedents exist in the literature,
and we will accordingly briefly touch upon the subject here.
Suppose we have devised a malgorithm which can run an arbitrary
amount of time before producing its result. The task now becomes
one of maximizing this time, subject to the constraints formed
by the finite MTBF of the hardware, and the equally finite tolerance
threshold of the person waiting for the result.
Definition 3: Any malgorithm which produces its output at the last
possible instant before either the hardware fails, or the user
terminates the program is a member of class "Epsilon".
As an aside, malgorithms of this class will usually require some
additions to the operating system to recognize an attempt to
cancel the program execution. Hardware modifications, in the
form of energy storage systems to permit the program to
print its output after the frustrated user has pulled the power
plug, will probably also be necessary.
It should be noted that malgorithms of class "Epsilon" have
an unfortunate flaw: since they produce output whenever they are
terminated by the user, they are also the fastest possible
algorithms for any problem, being limited only by the speed with
which the user can pull the plug. Once malgorithms of this class
have become established, future work in computational speedup
will likely focus on fast switches for power cutoff.
Now that we have defined some upper bounds on theoretical
malgorithm performance, we would like to define some additional
classes of actual malgorithms, primarily for taxonomic purposes.
The classes below are only a beginning, and the reader is invited
to contribute additional definitions and examples to the discussion.
The classes are not maximal or minimal in any sense, but merely define
some categories of malgorithms. Example malgorithms should be easily
recognized as falling into one or another of the classes defined.
Definition 4: Malgorithms which employ recursion to solve a problem
for which there exists a closed form solution are members of class
"Fibonacci".
Definition 5: Malgorithms which solve a problem by exhaustive generation
of all permutations, when there is any alternative solution, are
members of class "Salesman".
Definition 6: Malgorithms which apply a general algorithm to the wrong
size problem are members of class "Heapsort".
Example: Heapsort applied to the list 1,3,2.
Definition 7: Malgorithms for Monte-Carlo solutions to analytic
functions are members of class "Pi".
Definition 8: Malgorithms which provide a solution to a problem by
solving a more complex isomorphic problem are members of the class
"Gauss".
Example: Multiplication of two numbers by adding their logarithms.
Definition 9: Malgorithms which perform redundant computations
are members of class "Sheep".
Example: Determining the number of sheep in a herd by counting
the number of legs and dividing by four.
It should be noted that the classes proposed here are neither
exhaustive, nor are they mutually exclusive. Most current
programs contain algorithms which upon inspection are really
malgorithms that fall into one or more of the classes here
defined. It is our devout hope that this short note will lead to
a more intensive investigation of this much neglected area of
computer science. The author is convinced that this area
can provide subject matter for several Ph.D. dissertations
at the more mathematically rigorous institutions of higher
learning, and wishes to express his gratitude to the contributors
to the Ailist, who have given the impetus for this important work.
Biesel@Rutgers.ARPA
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Date: Thu, 8 Nov 84 11:30:22 cst
From: "Walter G. Rudd" <rudd%lsu.csnet@csnet-relay.arpa>
Subject: data structures + malgorithms =
It is clear that there are many more malgorithms than problems, if for no
other reason than we all have more solutions than problems. The real
science of malgorithms is to find really useful applications of good
malgorithms beyond the trivial ones of classroom and textbook examples.
To my surprise there really are such uses, or there is at least one.
The other day I was talking with an attorney about copyrighting programs.
He says that in copyright cases in which there is some question of
authorship, judges are often impressed by "fingerprints" embedded in
software. The usual kind of fingerprint is a copyright notice
buried in block 0 of an index file, variable names which form a code
for the author's name, etc. But he says the most effective fingerprints
are sections of code so poorly designed and written that their inclusion
in the software must have been intentional, since nobody would be stupid
enough to use such sloppy techniques in their normal practice.
In court, to prove you wrote the program, you simply point out the bad parts
to the judge and claim that, since you are an expert, the only way that code
could have gotten there was by your intentionally inserting a fingerprint.
A nice side effect of this technique is that we now have a good excuse to
give to grad students and others who discover malgorithms in our programs. We
simply say that we are preparing to protect our copyright.
So here we have the birth of a new discipline. Not only do we have the
design and analysis of malgorithms; we now have applications of malgorithms
as well. The question is, are there any other applications?
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Date: 3 Nov 1984 1201-PST
From: Rob-Kling <Kling%UCI-20B@UCI-750a>
Subject: Program Description - Social Impacts of Computing, UC-Irvine
CORPS
Graduate Education in
Computing, Organizations, Policy, and Society
at the University of California, Irvine
This graduate concentration at the University of California,
Irvine provides an opportunity for scholars and students to
investigate the social dimensions of computerization in a setting
which supports reflective and sustained inquiry.
The primary educational opportunities are PhD concentrations in
the Department of Information and Computer Science (ICS) and MS and
PhD concentrations in the Graduate School of Management (GSM).
Students in each concentration can specialize in studying the social
dimensions of computing.
The faculty at Irvine have been active in this area, with many
interdisciplinary projects, since the early 1970's. The faculty and
students in the CORPS have approached them with methods drawn from the
social sciences.
The CORPS concentration focuses upon four related areas of
inquiry:
1. Examining the social consequences of different kinds of
computerization on social life in organizations and in the larger
society.
2. Examining the social dimensions of the work and organizational
worlds in which computer technologies are developed, marketed,
disseminated, deployed, and sustained.
3. Evaluating the effectiveness of strategies for managing the
deployment and use of computer-based technologies.
4. Evaluating and proposing public policies which facilitate the
development and use of computing in pro-social ways.
Studies of these questions have focussed on complex information
systems, computer-based modelling, decision-support systems, the
myriad forms of office automation, electronic funds transfer systems,
expert systems, instructional computing, personal computers, automated
command and control systems, and computing at home. The questions
vary from study to study. They have included questions about the
effectiveness of these technologies, effective ways to manage them,
the social choices that they open or close off, the kind of social and
cultural life that develops around them, their political consequences,
and their social carrying costs.
CORPS studies at Irvine have a distinctive orientation -
(i) in focussing on both public and private sectors,
(ii) in examining computerization in public life as well as within
organizations,
(iii) by examining advanced and common computer-based technologies "in
vivo" in ordinary settings, and
(iv) by employing analytical methods drawn from the social sciences.
Organizational Arrangements and Admissions for CORPS
The CORPS concentration is a special track within the normal
graduate degree programs of ICS and GSM. Admission requirements for
this concentration are the same as for students who apply for a PhD in
ICS or an MS or PhD in GSM. Students with varying backgrounds are
encouraged to apply for the PhD programs if they show strong research
promise.
The seven primary faculty in the CORPS concentration hold
appointments in the Department of Information and Computer Science and
the Graduate School of Management. Additional faculty in the School
of Social Sciences, and the program on Social Ecology, have
collaborated in research or have taught key courses for CORPS
students. Research is administered through an interdisciplinary
research institute at UCI which is part of the Graduate Division, the
Public Policy Research Organization.
Students who wish additional information about the CORPS concentration
should write to:
Professor Rob Kling (Kling@uci)
Department of Information and Computer Science
University of California, Irvine
Irvine, Ca. 92717
714-856-5955 or 856-7403
or to:
Professor Kenneth Kraemer (Kraemer@uci)
Graduate School of Management
University of California, Irvine
Irvine, Ca. 92717
714-856-5246
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End of AIList Digest
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