January 10, 2006
AI Expert Newsletter -January 2006
Jocelyn Paine
Special issue celebrating 50th anniversary of the Dartmouth Summer Project on Artificial Intelligence; "Eightynine People, Three Programs, and a Computer" - AI recollections, memorabilia, predictions, papers.
Dr. Dobb's AI Expert Newsletter
AI - The art and science of making computers do interesting things that
are not in their nature.
Immortality Limited
Baking Logic By the Pound
We propose that a 2 month, 10 man study of artificial
intelligence be carried out during the summer of 1956 at Dartmouth
College in Hanover, New Hampshire. The study is to proceed on the
basis of the conjecture that every aspect of learning or any
other feature of intelligence can in principle be so precisely
described that a machine can be made to simulate it. An attempt
will be made to find how to make machines use language, form
abstractions and concepts, solve kinds of problems now reserved
for humans, and improve themselves. We think that a significant
advance can be made in one or more of these problems if a carefully
selected group of scientists work on it together for a summer.
These words begin the
PROPOSAL
FOR THE DARTMOUTH SUMMER RESEARCH PROJECT ON ARTIFICIAL INTELLIGENCE,
written by John McCarthy, Marvin Minsky,
Nathaniel Rochester and
Claude Shannon. The
Dartmouth
Summer
Project on Artificial Intelligence itself took place in 1956. In this
issue of the Newsletter, I celebrate its 50th anniversary.
I've taken eightynine people - mainly AI researchers - from
the 1920s to the present day, and collected from the Web
their memories of, views on, and predictions for,
AI. There are also a few memorabilia, and assorted papers to
demonstrate the diversity of approaches. In some
cases, very personal approaches, where the author
has strong views about how to advance AI by
striking away from current fashion.
Some papers come from before
the phrase "artificial intelligence" was coined.
Others might not have been considered AI by the Project's
founders. John McCarthy, for example,
says
one of the reasons for inventing the
term "artificial intelligence" was to escape association with "cybernetics".
However, I have included some cybernetics work,
because not only is it fascinating, but it demonstrates
the spirit of its time, and has almost certainly
influenced some AI research.
I'm obviously restricted to what's on the Web.
Unfortunately,
I found myself more restricted because
much of what I wanted was there, but wasn't on its authors'
Websites and wasn't free.
Bobrow and Brady's Artificial Intelligence 40 years later,
I found only on the site of its journal
Artificial Intelligence, at a cost of $30. That's
for 4 pages.
To discover how, in the 1940s and 1950s, Bobrow's colleague
Berkeley was applying symbolic
logic and building electromechanical computers, I'd have
had to pay $35 for Edmund Berkeley, Computers, and Modern
Methods of Thinking. Thus I've had to ignore some fine
papers which I could find only at sites such as ACM Portal,
IEEE, and Project Muse.
Even if I'd been able to afford the several hundred pounds needed
to examine them all, linking to them would
have been unfairly tantalising to readers without
institutional subscriptions.
This was irritating, unhelpful, a waste of search and composition time,
and deeply frustrating.
Any researchers reading this - please, get copies
of your papers onto your Web sites. Some organisations are
very good at doing so. I knew about MIT's
wonderful OpenCourseWare
resource; now I've discovered that the MIT
Computer Science and Artificial Intelligence Laboratory
has a
digital archive.
(Coincidentally, this starts with a paper by Bobrow, on
his classic 1964 Student
program for solving algebra problems stated in English.)
Such archives are just what I want when teaching - which is,
after all, what I'm doing in this Newsletter.
There are other resources on the Web. Good starting points
are the AAAI's pages on
History,
Interviews and Oral History,
and
Brief History.
The list in this Newsletter isn't intended to be comprehensive; it's
just
what I could glean in a reasonable time. Send me links you think
I should include, and
when I've received enough, I may publish an updated version.
I have a bet with another member of St Peter's, my college, that
we shall achieve AI capable of human-equivalent conversation within
50 years. We are to meet in the College Bar, and the winner has to
hand over money equivalent to what was £10 when the bet was made.
If I remember correctly, that was 18th June 1986. I hope the next
30 years will enable me to raise a few pints to AI.
polaris.gseis.ucla.edu/pagre/ -
Agre's home page.
www.csc.liv.ac.uk/~mjw/pubs/ker95/subsubsectionstar3_3_2_2.html
Intelligent Agents: Theory and Practice by
Michael Wooldridge
and
Nick Jennings:
"At about the same time as
Brooks was describing his first results
with the subsumption architecture, Chapman was completing his Master's
thesis, in which he reported the theoretical difficulties with planning
... and was coming to similar conclusions about the inadequacies
of the symbolic AI model himself. Together with his co-worker Agre, he began to
explore alternatives to the AI planning paradigm.
Agre observed that most everyday activity is 'routine' in the sense that it requires little -
if any - new abstract reasoning. Most tasks, once learned, can be accomplished in a routine way,
with little variation. Agre proposed that an efficient agent architecture could be based on the
idea of 'running arguments'. Crudely, the idea is that as most decisions are routine,
they can be encoded into a low-level structure (such as a digital circuit), which
only needs periodic updating, perhaps to handle new kinds of problems. His approach
was illustrated with the celebrated PENGI system. PENGI is a
simulated computer game, with the
central character controlled using a scheme such as that outlined above."
www.stanford.edu/group/SHR/4-2/text/agre.html
the soul gained and lost -
artificial intelligence as a philosophical project, from
Constructions of the Mind:
Artificial Intelligence and the Humanities.
Volume 4, Issue 2 of Stanford Humanities Review, 1995:
"To watch the dynamics of this process unfold, it will
help to consider one final chapter: the STRIPS program.
The purpose of STRIPS is to automatically derive "plans" for a
robot to follow in transporting objects around in a maze of rooms. The
program constructs these plans through a search
process modeled on those of
Newell and Simon. ...
To those who have had experience getting complex symbolic programs to work,
the STRIPS papers make intense
reading. Because the authors were drawing together so many software
techniques for the first time, the
technically empathetic reader gets a vivid sense of struggle: the unfolding
logic of what the authors
unexpectedly felt compelled to do, given what seemed to be required to
get the program to work."
polaris.gseis.ucla.edu/pagre/critical.html
Toward a Critical Technical Practice:
Lessons Learned in Trying to Reform AI, online version of
Agre's chapter in Bridging the Great Divide: Social Science,
Technical Systems, and Cooperative Work, edited by
Geof Bowker, Les Gasser, Leigh Star, and Bill Turner, 1997.
www.cs.rochester.edu/u/james/ -
Allen's home page.
www.aaai.org/Library/Magazine/Vol19/19-04/vol19-04.html
Page linking to
AI Growing Up: The Changes and Opportunities,
edited transcript of AAAI Keynote Address
in Providence, 1997; AI Magazine
Volume 19, Issue 4, Winter 1998:
"AI has always been a strange field. Where
else could you find a field where people
with no technical background feel completely
comfortable making claims about viability
and progress? We see articles in the popular
press and books regularly appear telling us
that AI is impossible, although it is not clear
what the authors of these publications mean
by that claim. Other sources tell us that AI is
just around the corner or that it's already with
us. Unlike fields such as biology or physics,
apparently you don't need any technical
expertise in order to evaluate what's going on
in this field.
But such problems are not limited to the
general public. Even within AI, the researchers
themselves have sometimes misjudged the difficulty
of problems and have oversold the
prospects for short-term progress based on initial
results. As a result, they have set themselves
up for failure to meet those projections.
Even more puzzling, they also downplay successes
to the point where, if a project becomes
successful, it almost defines itself out of the
field. An excellent example is the recent success
of the chess-playing program DEEP BLUE,
which beat the world chess champion in 1997.
Many AI researchers have spent some effort to
distance themselves from this success, claiming
that the chess program has no intelligence
in it, and hence it is not AI. I think this is simply
wrong and will spend some time trying to
argue why.
So how can we explain this strange behaviour?"
act-r.psy.cmu.edu/people/ja/ -
Anderson's home page.
act-r.psy.cmu.edu/papers/97/ACT.ASimpleTheory.pdf
ACT: A simple theory of complex cognition. American Psychologist,
Volume 51, 1996:
"We (e.g., Anderson, Boyle, Corbett, & Lewis, 1990; Anderson,
Corbett, Koedinger, & Pelletier, 1995; Anderson & Reiser, 1985) have
created computer-based instructional systems, called intelligent tutors, for
teaching cognitive skills based on this kind of production-rule analysis
[of students learning to write recursive programs]. By
basing instruction on such rules, we have been able to increase students'
rate of learning by a factor of 3. Moreover, within our tutors we have
been able to track the learning of such rules and have found that they
improve gradually with practice ....
Our evidence indicates that underlying the complex, mystical skill of
recursive programming is about 500 rules like the one above, and that
each rule follows a simple learning curve ....
This illustrates the major claim of this article: All that
there is to intelligence is the simple accrual and tuning of
many small units of knowledge that in total produce complex
cognition. The whole is no more than the sum of its parts, but it has a lot of parts.
The credibility of this claim has to turn on whether we can
establish in detail how the claim is realized in specific
instances of complex cognition. The goal of the ACT theory,
which is the topic of this article, has been to establish the
details of this claim. It has been concerned with three principal
issues: How are these units of knowledge represented, how are they
acquired, and how are they deployed in cognition?"
www.cnl.salk.edu/~tony/
Bell's home page (last updated 2000):
"My long-term scientific goal is to try to work out how the
brain learns (self-organises). This took me in directions of
Information Theory and probability theory for neural networks.
This provides a hopelessly crude and impoverished model (called redundancy
reduction) of what the brain does and how it lives in its world. Unfortunately,
it's the best we have at the moment. We have to do some new mathematics before
we reach self-organisational principles that will apply to the physical
substrate of the brain, which is molecular: ion channels, enzyme complexes,
gene expression networks. We have to think about dynamics, loops, open systems,
how open dynamical systems can
encode and effect the spatio-temporal trajectories of their perturbing inputs."
www.cnl.salk.edu/~tony/ptrsl.pdf
Bell's home page continues with
his invited contribution to the special
Millennial issue of the Philosophical Transactions of the Royal Society of London,
in which contributors were asked to predict the future of their
research and its effects on society:
Levels and loops: the future of artificial
intelligence and neuroscience,
Philosophical Transactions of the Royal Society of London B,
Volume 354, 1999.
Given the many levels of
explanation required in neuroscience, from neural spike signals down to the effect of proteins'
electrical interactions, can we separate the brain's hardware level
from its software level, or is this kind of hardware/software independence
impossible?
Bell concludes that:
"AI and neuroscience are exactly placed where the
deaths of dualism and feed-forward thinking are scheduled to take place.
If these disciplines choose to participate
in this shift, rather than cling to concepts that are
not empirically supported, then there will be many interesting PhD theses to write."
vorlon.cwru.edu/~beer/ -
Beer's home page.
www.ecs.soton.ac.uk/~harnad/Tp/robot.html
Is it an ant? A cockroach? Or Simply a Squiggle?, by
Stephen Strauss, The Toronto Globe and Mail, c. 1990.
Popular feature on the work of Beer and others:
"'Even the simplest animals are better at changing their behaviour to
cope with the real world than the most sophisticated robot today', says
Randall Beer, a computer scientist at Case Western Reserve University in Cleveland.
To many researchers, this interest in animal models has a clear evolutionary rationale.
'Nature never evolved a brain and then built the first body around it.
That is nonsense' says University of Waterloo engineer Mark Tillen."
www.cs.cmu.edu/afs/cs/project/ai-repository/ai/areas/neural/systems/nerves/0.html
NERVES: Nervous System Construction Kit,
from the CMU AI Repository.
This directory contains NERVES, the nervous system construction kit.
It includes a computer simulation of the real-time behavior of a simplified cockroach,
based on Beer's work.
vorlon.cwru.edu/~beer/Papers/TICS.pdf
Dynamical approaches to cognitive science
Trends in Cognitive Sciences, Volume 4, Issue 3,
2000.
Beer reviews three contrasting
examples of work on dynamical ideas in cognition,
using these to articulate the
main differences between dynamical approaches and the symbolic and
connectionist approaches:
"In a second experiment, Elman extended this work to
longer and more complex sentences with long-distance dependencies
involving number agreement, verb argument
structure, and relative clauses. The dynamics of a network
trained on the prediction task was then examined by plotting
projections of the trajectories of hidden-unit activation produced
by sample sentences. The trajectory produced by the
sentence 'Boy who chases boy chases boy' is shown ...
Note that occurrences of the same word at different points
in the sentence leave the network in different states. These
differences in network state correspond to the network's
memory of the information required to process long-distance
dependencies correctly. Because the local dynamics at each
point determine the effect that subsequent words can have on
the network state, grammatical constraints are manifested
in the structure of the network dynamics itself. Thus, as a
sentence is processed, each word drives the network along
one of the different trajectories allowed by the dynamics at
that point, with context manifested as variations in state that
influence subsequent processing."
www.soc.uiuc.edu/people/CVPubs/pickerin/cybernetics.pdf
Cybernetics and the Mangle:
Ashby, Beer and
Pask, by
Andrew Pickering, University of Illinois, 2002.
This paper about the three cyberneticists contains a
fascinating account of Beer's work:
"Beer, perhaps more than anyone else, believed that the
homeostat held out the promise of constructing superhuman
brains, and I first want to emphasise the variety of materialisations of
homeostat-type set-ups that Beer contemplated, and often built, in the
1950s and early 1960s. In 1956, for example, he devised a game for
solving simultaneous linear equations ...
The key feature of this game was that it could be played by children who
did not know the relevant mathematics. The children would make selections
from various alternative moves, and their choices would be encouraged or
discouraged by what Beer called algedonic feedback - in this case, coloured
lights signifying pleasure or pain at whatever moves the
children made. In effect, the children were the
material basis of an adaptive or self-organising system
that could be trained to perform the relevant calculations
without having to be explicitly 'programmed' to do so.
Beer then moved on from children to mice, thinking that
mice could be trained to solve simultaneous equations, too.
It is not clear whether this worked or not, but I do believe
this mouse-computer eventually moved into popular culture,
having a role in Douglas Adams' book The Hitch-Hiker's
Guide to the Universe. It certainly features in a recent
novel in Terry Pratchett's Discworld series. A rather general point here, I suppose, is that
cybernetics had a sense of humour -
one of its many differences from the classical science paradigm."
He apparently also tried to use the water-flea Daphnia and the
single-celled Euglena as homeostatic systems.
www.chroniclesofwizardprang.com/
Beer's Chronicles of Wizard Prang, 1989. From the
Cwarel Isaf Institute
for management
cybernetics.
"Wizard Prang was threatened by toast.
He knew that he was supposed to eat breakfast. It was good for him.
But eating was exactly what he did not want to do early in the morning."
www.guardian.co.uk/chile/story/0,13755,1037547,00.html
Santiago dreaming, by Andy Beckett,
The Guardian,
8th September, 2003.
"During the early 70s, in the
wealthy commuter backwater of West Byfleet
in Surrey, a small but rather remarkable experiment
took place. In the potting shed of a house called
Firkins, a teenager named Simon Beer, using bits of
radios and pieces of pink and green cardboard,
built a series of electrical meters for measuring public opinion."
The story of Beer's Project Cybersyn in Chile, an attempt
to "implant" an electronic "nervous system" into an entire country,
not long before
the Allende deposal.
Berkely was coeditor with Daniel Bobrow of
the classic
The
Programming Language LISP: Its Operation and Applications.
A Berkeley timeline
suggests that he had an interest in symbolic computing much earlier,
having written memoranda on the applications of symbolic logic in 1941.
In 1948, he organised Berkeley Enterprises, Inc., which
began as a consulting firm and later sold construction kits for
building robots and computing devices as well as publications on logic and cybernetics.
One of these kits was "Simon",
described in the
Fact Sheet on
"Simon"
as "A very simple model, mechanical brain - the smallest complete mechanical brain in existence".
The fact sheet
continues
"We shall now consider how we can design a very simple
machine that will think.. Let us call it Simon, because of its
predecessor, Simple Simon... Simon is so simple and so small in fact that it could
be built to fill up less space than a grocery-store box; about four cubic feet....It may
seem that a simple model of a mechanical brain like Simon is of no great practical use. On the contrary,
Simon has the same use in instruction as a set of simple chemical experiments has:
to stimulate thinking and understanding, and to produce training and skill. A training
course on mechanical brains could very well
include the construction of a simple model mechanical brain, as an exercise". In
fact, in his conclusion, Berkeley hopes that Simon might start
a fad of building baby mechanical brains, similar to the crystal-set fad of the 1920s.
Amongst the points that make Simon unique are:
"it can be carried around in one hand (and the power supply in the other hand)";
"it is a mechanical brain that has cost less than $1,000"; and
"it is an excellent device for teaching, lecturing and explaining".
From the pages of Berkeley's 1949 book Giant Brains or Machines That Think
reproduced at
www.newbegin.com/html/misc__item_detail_5.html,
we see that
Simon was a relay machine using paper tape for input
and lights for output.
What originally drew me to include Berkeley in this newsletter
was his 1956
SMALL ROBOTS - REPORT.
It's an interesting and fairly detailed description of a number of electromechanical
machines. These include Squee (named after "squirrel"), a robot squirrel which will
hunt and pick up tennis-ball "nuts". Squee uses
phototubes and contact switches as sensors, three motors as effectors, and half a dozen
relays as "brain". Most of the robots are games,
intended as show-stopping demonstrations of electronic wonder:
there's a maze-solving robot with magnetic-drum memory, a Noughts-and-Crosses
machine, and a Divorce Mill with Bigamy Alarm.
The robots were not intended only as show-stoppers.
Berkeley says he has
a second and perhaps more scientific purpose: to explore the intelligent behavior of machines and master their techniques.
community.computerhistory.org/scc/projects/LISP/book/III_LispBook_Apr66.pdf
The Programming Language LISP: Its Operation and Applications, edited
by Bobrow and Berkeley, 1964, 1966.
www.blinkenlights.com/classiccmp/berkeley/
Edmund Berkeley timeline.
www.blinkenlights.com/classiccmp/berkeley/simonfaq.html
Fact Sheet on "Simon".
www.newbegin.com/html/misc__item_detail_5.html
Cover and four pages of Berkeley's 1949 book Giant Brains or Machines That Think.
www.blinkenlights.com/classiccmp/berkeley/report.html
Berkeley's SMALL ROBOTS - REPORT, 1956.
www.w3.org/People/Berners-Lee/ -
Berners-Lee's home page.
64.28.79.69/read/swiftkick/column.html?ArticleID=421
The Semantic Argument Web -
What really scares me,
by David Weinberger, 14th June, 2002.
The author fears that, although Berners-Lee claims the Semantic Web is not AI,
it is dragging him into one of AI's stickiest morasses - knowledge
representation.
www.w3.org/DesignIssues/Semantic.html
Semantic Web Road map, 1998.
Berners-Lee talks about RDF as a logic language. This page
links to What the Semantic Web can represent,
www.w3.org/DesignIssues/RDFnot.html,
which states that "A Semantic Web is not Artificial Intelligence". I suspect not
everyone will agree.
www2.parc.com/spl/members/bobrow/ -
Bobrow's home page.
ftp://publications.ai.mit.edu/ai-publications/pdf/AIM-051.pdf
METEOR: A LISP Interpreter for String Transformations.
Memo 51, Artificial Intelligence Projects, RLE and MIT Computation Center,
April 24, 1963.
This is
an earlier version of the two articles
The LISP Program for METEOR
and
METEOR: A LISP Interpreter for String Transformations printed
in
The Programming Language Lisp : Its Operation and Applications.
Meteor was a pattern-matching extension to Lisp, inspired by
Yngve's
Comit language. Bobrow wrote Student, his classic program for solving simple algebra problems
stated in English, in it. The Meteor paper notes that lists containing
more than 16,000 atoms would not fit into the 7090.
www.lcs.mit.edu/specpub.php?id=573
Natural Language Input for a Computer Problem Solving System,
MIT-LCS Technical Report 001, by Bobrow, 1964.
The original report about Student. From its number, this looks like the starting point, of an
important MIT series.
www.cs.berkeley.edu/~bh/v3ch6/ai.html
Artificial Intelligence, by Brian Harvey,
University of California, Berkeley. A chapter from Beyond Programming, volume 3 of
Harvey's Computer Science Logo Style (2nd edition), 1997.
This chapter analyses Student and translates it into Logo.
www.nickbostrom.com -
Bostrom's home page.
www.nickbostrom.com/superintelligence.html
How Long Before Superintelligence?
1997, 1998; postscripts added 2000 and 2005.
Originally published in International Journal of Future Studies, Volume 2, 1998.
To be reprinted in
Linguistic and Philosophical Investigations, March 2006.
Bostrom, director of the Future of Humanity Institute
at Oxford University,
outlines the case for believing that we will have
superhuman artificial intelligence within the first third of the next century.
people.csail.mit.edu/brooks -
Brooks's home page.
http://people.csail.mit.edu/brooks/papers/AIM-1293.pdf
Intelligence Without Reason,
MIT AI Lab Memo 1293 (1991), prepared for
Proceedings of the 12th International Joint Conference on Artificial Intelligence (IJCAI-91):
"Computers and Thought are the two categories that together define Artificial
Intelligence as a discipline. It is generally accepted that work in Artificial
Intelligence over the last thirty years has had a strong influence on aspects
of computer architectures. In this paper we also make the converse claim;
that the state of computer architecture has been a strong influence on our
models of thought. The Von Neumann model of computation has lead Artificial
Intelligence in particular directions. Intelligence in biological systems
is completely different. Recent work in behavior-based Articial Intelligence has produced new models of
intelligence that are much closer in spirit to biological systems. The non-Von Neumann
computational models they use share many characteristics with biological computation."
people.csail.mit.edu/brooks/papers/nature.pdf
The relationship between matter and life,
Nature, Volume 409, January 2001.
The paper above was an early account of
the behaviour-based approach to AI. Ten years later,
Brooks asks why,
although they are much more lifelike than
the pure engineering artefacts of traditional
AI, the systems built under the
behaviour-based and Artificial Life approaches do
not seem as alive as we might hope. Why,
despite the computer power we now have at our disposal,
are we not good at modelling living systems? What
is the fundamental gap in our understanding?
www.paul-brown.com/ -
Brown's home page.
www.paul-brown.com/WORDS/CR2003.PDF
The Idea Becomes a Machine
AI and Alife in Early British Computer Arts, 2003.
Brown discusses the influence of AI and Artificial Life on the
computer arts in the UK up to around 1980, focussing on
work at the Slade School of Art, and including the
1968 Cybernetic Serendipity exhibition at the Institute of
Contemporary Art. This essay was written as part of the
CACHe (Computer Arts, Contexts, Histories, etc) project, looking at
the early days of the computer arts in the UK.
consc.net/chalmers/ -
Chalmers's home page.
consc.net/papers/matrix.html
The Matrix as Metaphysics.
If one thing is certain, it's that AI will give rise to
philosophical questions about consciousness.
If another thing is certain, it's that
Hollywood will never understand AI *.
But we can at least use one to teach about the other:
"This paper was written for the philosophy section of
the official Matrix website. As such, the bulk of the
paper is written to be accessible for an audience without a
background in philosophy. At the same time, this
paper is intended as a serious work of philosophy,
with relevance for central issues in epistemology,
metaphysics, and the philosophy of mind and language.
A section of 'philosophical notes' at the end
of the article draws out some of these connections explicitly."
whatisthematrix.warnerbros.com/
Warner Brothers Matrix site.
consc.net/online.html
Online papers on consciousness,
compiled by Chalmers.
fragments.consc.net/
Chalmers's blog.
(*) Or any other science.
www.cogs.susx.ac.uk/users/ronc/ -
Chrisley's home page.
www.cogs.susx.ac.uk/users/ronc/papers/ai.txt
Artificial intelligence,
an entry by Chrisley for The Oxford Companion to the Mind (second edition),
edited by Richard Gregory, 2004:
"Since the mid-1980s, there has been sustained development of the core ideas of
artificial intelligence, e.g., representation, planning, reasoning, natural
language processing, machine learning, and perception. In addition, various
sub-fields have emerged, such as research into agents (autonomous, independent
systems, whether in hardware or software), distributed or multi-agent systems,
coping with uncertainty, affective computing/models of emotion, and ontologies
(systems of representing various kinds of entities in the world) - achievements
which, while new advances, are conceptually and methodologically continuous with
the field of artificial intelligence as envisaged at the time of its modern
genesis: the Dartmouth conference of 1956.
However, a substantial and growing proportion of research into artificial
intelligence, while often building on the foundations just mentioned, has
shifted its emphasis. ...
The new developments, which have
their roots in the cybernetics work of the 40s
and 50s as much as, if not more than they do in mainstream AI, can be divided
into two broad areas: adaptive systems, and embodied/situated approaches."
Chrisley goes on to survey these two areas, and
the relevance of AI to understanding the mind.
bill.clancey.name/ -
Clancey's home page.
cogprints.org/292/00/126.htm
Notes on
"Epistemology of a Rule-based Expert System",
Artificial Intelligence, Volume 59, 1993 - special
issue Artificial Intelligence in Perspective.
Clancey writes about how his time with Mycin
led him to go beyond the simple
backward-chaining
explanation of its conclusions given by it and many other
expert systems.
www.cogs.indiana.edu/people/homepages/clark.html -
Clark's home page.
www.cogs.indiana.edu/andy/AIandFacesofReason.pdf
Artificial Intelligence and the Many Faces of Reason,
in
The Blackwell Guide To Philosophy Of Mind, edited by S. Stich
and T. Warfield, 2003.
"I shall focus this discussion on one small
thread in the increasingly complex weave of Artificial Intelligence and
Philosophy of Mind: the attempt to explain how rational thought is
mechanically possible. This is, historically, the crucial place where
Artificial Intelligence meets Philosophy of Mind. But it is, I shall
argue, a place in flux. For our conceptions of what rational thought
and reason are, and of what kinds of mechanism might explain them,
are in a state of transition. To get a sense of this sea change, I
shall compare several visions and approaches, starting with what
might be termed the Turing-Fodor conception of mechanical reason,
proceeding through connectionism with its skill-based model of reason,
then moving to issues arising from robotics, neuroscientific studies of
emotion and reason, and work on 'ecological rationality'. As we shall
see there is probably both
more, and less, to human rationality than originally met the eye."
www.cogs.indiana.edu/andy/tacrfinalw-Grush.pdf
Towards a Cognitive Robotics (with Rick Grush), Adaptive Behavior,
Volume 7, Issue 1, 1999:
"Contemporary cognitive science, it is fair to say, displays
a deep-seated commitment to a representational
view of the mind. According to such a view, intelligence
is largely a matter of problem solving, and problem-
solving is carried out via computations defined over
internal representations of salient real-world structures,
facts and hypotheses. ...
This picture may be dubbed, without malice, the same
old story (SOS). Classic statements of SOS include, e.g.,
Pylyshyn, 1987; Fodor 1975, 1987. But the same broad
outline applies equally to the bulk of work in
connectionism and neural networks (Rumelhart,
McClelland, & The PDP Research Group, 1986;
Smolensky, 1988; Elman, 1993; Churchland &
Sejnowski, 1992). Nevertheless, scepticism concerning
SOS is undoubtedly on the rise. In particular, there is a
definite challenge in the air regarding the pivotal notion
of internal representation itself."
www.hpl.hp.com/features/featured_inventors/dave_cliff.html
Dave Cliff:
On "Articulate Rebels With Brains",
HP Labs Featured Inventor,
February 2003.
Cliff has worked in artificial
life and evolutionary robotics. He joined Hewlett-Packard six
years ago; in this HP inventor profile, he
talks about inspiring children to
be inventors.
news.bbc.co.uk/1/hi/england/1658983.stm
Scientists invent electronic DJ, BBC.
Friday, 16 November, 2001.
Cliff's robot disc jockey.
www.lim.univ-mrs.fr/~colmer/tablematiere.html -
Colmerauer's home page.
www.lim.univ-mrs.fr/~colmer/ArchivesPublications/HistoireProlog/19november92.pdf
The birth of Prolog, November 1992.
The authors describe how Prolog was invented -
in a project aimed not at producing a
programming language, but at processing natural language.
www.lim.univ-mrs.fr/~colmer/ArchivesPublications/HistoireProlog/24juillet92.pdf
La naissance de Prolog, July 1992.
The original, French, version of this paper.
www.gmd.de/People/Jared.Darlington/ -
Darlington's home page.
www.gmd.de/People/Jared.Darlington/Boston
Boston, 2001.
An account of the early 1960s, a heady time:
"... there was a definite feeling of being where it's happening.
At MIT, time-sharing on IBM 7090s and 7094s was getting off the ground,
allowing users effectively to
run and debug programs on-line, and other applications of such large
new mainframes were being explored. Under
Marvin Minsky's
direction, research on artificial intelligence was well under way at
Tech Square amid speculation as to how soon we will 'have AI'."
(Page is in HTML but lacks an appropriate extension, so your browser may display
the HTML verbatim.)
ase.tufts.edu/cogstud/~ddennett.htm
Dennett's home page. See it not only for Dennett's research and
publications - The Mind's I, coedited with Douglas Hofstadter, is a
well-known book - but also for the
photos of a 1950s French robot dog. Dennett would
be pleased to receive any substantiated information about its provenance.
mitpress.mit.edu/e-books/Hal/chap16/sixteen1.html
When HAL Kills, Who's to Blame?
Computer Ethics,
in
Hal's Legacy:
2001's Computer as Dream and Reality, edited by
David Stork, 2001:
"If we want to trace the skein of moral
responsibility in the actions of HAL, recent
fiction has provided us with models - from
RoboCop, to Max Headroom, to Blade Runner,
which may help us understand the kinds of
issues which we need to face in this kind of
study. What issues
would come in to play if we make moral judgements
on HAL's behavior?"
pp.kpnet.fi/seirioa/cdenn/hofstadt.htm
Review of
Hofstadter et al., "Fluid Concepts and Creative Analogies",
Complexity, 1995.
"Hofstadter has numerous important reflections to
offer on 'the knotty problem of evaluating research,' and one of the book's
virtues is to draw clearly for us 'the vastness of the gulf that can separate
different research projects that on the surface seem to belong to the same field.
Those people who are interested in results will begin with a standard technology,
not even questioning it at all, and then build a big system that solves many
complex problems and impresses a lot of people.' He has taken a different
path, and has often had difficulties convincing the grown-ups that it is a good one:
'When there's a little kid trying somersaults out for the first time next to a flashy
gymnast doing flawless flips on a balance beam, who's going to pay
any attention to the kid?' A fair complaint, but part of the
problem, now redressed by this book, was that the little kid didn't
try to explain (in an efficient format accessible to impatient grown-ups)
why his somersaults were so special."
Are your somersaults special??
www.cs.utexas.edu/users/EWD/transcriptions/EWD04xx/EWD448.html
Trip report E.W.Dijkstra, Edinburgh and Newcastle, 1 - 6 September 1974.
"On Sunday 1st September 1974 I flew via London from Amsterdam to Edinburgh ...
Monday morning I passed at the Department of Machine Intelligence, Hope Park Square
...
The more I hear about Artificial Intelligence the more ridiculous becomes
its often heard defense that Artificial Intelligence has contributed so much to
programming technology - for both, the claim and its debunking, see the various
contributions to the Lighthill Report.
I see more and more reason to characterize its contribution as 'adding to the confusion'".
www.cs.utexas.edu/users/EWD/transcriptions/EWD06xx/EWD665.html
Trip report E.W.Dijkstra, U.K. - Bahamas - U.S.A., 11-30 April 1978.
"On our 'afternoon off' I did not tour the countryside -
although I knew it to be very beautiful - but had a long
discussion with prof. R.M.Burstall from Edinburgh. ...
The reason was that earlier this year I had had to referee
a couple of papers with a strong flavour of Artificial Intelligence.
In both cases I had recommended rejection because, according
to my scientific standards, they did not have enough 'meat' in
them. After I had done so a number of times in succession, I got a
little worried, and wanted to know whether the superficiality
observed was only characteristic of the authors in question, or was
typical for the whole field. As I was fearing the latter I wanted to give
Artificial Intelligence a last chance before definitely rejecting it..."
ist-socrates.berkeley.edu/~hdreyfus/ -
Dreyfus's home page.
www-formal.stanford.edu/jmc/reviews/dreyfus/dreyfus.html
Review of
Hubert Dreyfus's book What Computers Still Can't Do, by
John McCarthy.
"In the first edition of Dreyfus's book there were some challenges
to AI. Dreyfus said computers couldn't exhibit 'ambiguity tolerance',
'fringe consciousness' and 'zeroing in'. These were left so imprecise
that most readers couldn't see any definite problem at all. In the succeeding
30 years Dreyfus has neither made these challenges more precise nor proposed
any new challenges, however imprecise. It's a pity, because AI could use a
critic saying, 'Here's the easiest thing
I don't see how you can do'."
McCarthy's review includes sections on progress in, and the future
of, logic-based AI; and on common sense in Lenat's
work - "one of the few workers in AI at
whose recent work Dreyfus has taken a peek". He quotes Dreyfus:
"While representationalists have written programs that
attempt to deal with each of these problems
[in representing and reasoning with common-sense
knowledge], there is no generally accepted solution, nor
is there a proof that these problems cannot be solved. What is clear
is that all attempts to solve them have run into unexpected difficulties, and
this in turn suggests that there may well be in-principle limitations on
representationalism. At the very least these difficulties lead us to question
why anyone would expect the representationalist project to succeed."
Why, as McCarthy says, should one expect such work to be easy?
www.pbs.org/newshour/bb/entertainment/jan-june97/big_blue_5-12.html
BIG BLUE WINS,
May 12, 1997. Transcript of a discussion on PBS between
Gary Kasparov, Frederic Friedel (Kasparov's Adviser),
C. J. Tan, (Deep Blue Programmer),
Daniel Dennett,
Dreyfus,
Jim Lehrer,
Paul Solman, and
Margaret Warner.
Dreyfus claims that although in a chess world, the computer will always beat people,
"in a world in which relevance and intelligence play a crucial role and
meaning in concrete situations, the computer has always behaved miserably,
and there's no reason to think that that will change with this victory."
www.slate.com/id/3650/entry/23905/
www.slate.com/id/3650/entry/23906/
Artificial Intelligence - mails between
Hubert Dreyfus
and Daniel Dennett, in Slate's
E-mail debates of newsworthy topics, 1997.
These emails concern
the PBS AI debate above.
gregegan.customer.netspace.net.au/index.html -
Egan's home page.
gregegan.customer.netspace.net.au/MISC/ORACLE/Oracle.html
Oracle, 1987.
First published in Asimov's Science Fiction, July 2000.
Under Turing, I link to
Andrew Hodges's
Turing Day lecture on what Turing would have done
had he lived beyond 1954. Oracle reshapes Turing's
life in a different way. In a slightly alternate universe, it evokes the era when the
British Government made Turing's life a sin. But Egan knows
his maths, physics and computing as well as his history. There's a BBC debate
between the alternate Turing and an alternate C. S. Lewis,
in which appears a proof of the
Halting Problem.
And Egan shows what might have happened if, with the help
of some very advanced AI, we were able to advance
20th Century technology as much as, for the good of humanity, he
must wish we were able to.
www.stanford.edu/group/SHR/4-2/text/dialogues.html
dialogues with colorful personalities of early ai,
by Güven Güzeldere and Stefano Franchi,
from
Constructions of the Mind:
Artificial Intelligence and the Humanities.
Volume 4, Issue 2 of Stanford Humanities Review, 1995:
Sample dialogues from these three
famous interactive programs.
www.amazon.co.uk/exec/obidos/ASIN/047191293X/026-0473756-9838829
Star Wars: A Question of Initiative, 1987.
Ennals managed information technology research
in the UK Government
Alvey Programme,
but resigned when the
Pentagon sought to use this research for
the Strategic Defense Initiative. In this book,
he wrote about how
current political systems are
inadequate for coping with the advanced technology - computing and AI
included - used
in projects such as SDI.
www.atarimagazines.com/creative/v9n11/220_Logic_and_recursion_the_.php
Logic and recursion: the prolog twist, by Jesse M. Heines, Jonathan Briggs, and Richard Ennals.
Creative Computing, Volume 9, Number 11, November 1983.
This early 1980s feature introduces Prolog and recursion to
users of such microcomputers as the Sinclair Spectrum, the BBC, the Apple, and the
Commodore 64.
ershov.iis.nsk.su/archive/eaindex.asp?lang=2&gid=286
Academician A. Ershov's archive.
Ershov was one of the visitors to the
1958 Symposium on the Mechanization of Thought
Processes at the National Physical Laboratory in Britain.
This archive contains a variety of memorabilia, including
talks given by Ershov, luggage tickets in English and Russian,
a demonstration of English Electric's Deuce computer,
questions composed by Members of Parliament, and a
souvenir programme
of Norman Wisdom in Where's Charley?
www.cs.washington.edu/homes/etzioni/ -
Etzioni's home page.
www.findarticles.com/p/articles/mi_m2483/is_n2_v18/ai_20392078
Moving up the information food chain: deploying softbots on the World Wide Web,
AI Magazine, Summer 1997.
"I view the World Wide Web as an information food chain.
The maze of pages and hyperlinks that comprise the Web are at the very bottom of the chain.
The WEBCRAWLERS and ALTAVISTAS of the world are information herbivores; they
graze on Web pages and regurgitate them as searchable indices. Today, most Web users feed near the
bottom of the information food chain, but the time is ripe to move up."
ksl-web.stanford.edu/people/eaf/ -
Feigenbaum's home page (last updated 1998).
www.forbes.com/global/1998/1130/0118096a.html
Artificial intelligence gets real, Daniel Lyons, Forbes Global, November 30, 1998.
"On a recent visit to the doctor, Edward Feigenbaum had the
eerie experience of seeing one of his inventions used in a
way he never expected: His 25-year-old concept was being used to diagnose a problem with his own breathing.
'It's using artificial intelligence,' the doctor patiently explained about the spirometer, which measures airflow.
'Oh, I see,' said Feigenbaum."
The feature tells of the birth of expert systems:
"Feigenbaum [in contrast to
researchers who were teaching computers to solve logic puzzles and play chess]
succeeded by thinking small. Unlike his rivals, he didn't
set out to recreate all of human intelligence in a computer. His idea was
to take a particular expert - a chemist, an engineer, a pulmonary
specialist - and figure out how that person solved a single narrow problem.
Then he encoded that person's problem-solving
method into a set of rules that could be stored in a computer."
www-db.stanford.edu/pub/voy/museum/feigentree.html
Tree (incomplete) of Feigenbaum's students, 2005,
from the
Stanford Computer History exhibits.
sulcus.berkeley.edu/FreemanWWW/manuscripts/ID6/92.html
Tutorial On Neurobiology: From Single Neurons To Brain Chaos,
International Journal of Bifurcation and Chaos, Volume 2, Number 3, 1992.
Chaos theory became fashionable in the late 1980s. In cognitive
science, a famous chaos-related paper was Skarda and Freeman's
How brains make chaos in order to make sense of the world, Behavioral
and Brain Sciences, Volume 10, 1987. The paper linked here
is a tutorial by Freeman on the subject:
"This review opens a window onto an approach through neurobiology to
nonlinear brain dynamics. It was written with a deep conviction that
collaboration between mathematicians, physicists, engineers and biologists
holds the key to understanding some of the most fascinating secrets of the central
nervous system. It follows a path from the elementary unit of the brain, the neuron,
to one of the more complicated networks of neural populations, the cerebral cortex. It
emphasizes the need for a two-level approach to brain function. The neuron is seen as the
microscopic element for integration and transmission, whereas the neural population is viewed
as the macroscopic element for the organization of behavior. As we proceed from neurons toward
networks of populations we gain a hierarchical perspective that enables us to understand
how chaotic activity can exist at multiple levels: subcellular organelles, neurons, networks,
populations, and brain systems, all of which are found in the cerebral cortex. Information
can be exchanged across levels at differing time and distance scales.
What roles might chaos play in brain function? We will conclude
that chaotic dynamics makes it possible for microscopic sensory input that is
received by the cortex to control the macroscopic activity that
constitutes cortical output, largely owing to the selective sensitivity
of chaotic systems to small fluctuations, and their capacity for rapid state transitions."
nepenthes.lycaeum.org/Misc/chaos.html
The Importance of Chaos Theory in the Development of Artificial Neural Systems,
by Dave Gross, probably written
in 1991 or 1992.
A short summary of chaos as Skarda and Freeman apply it.
en.wikipedia.org/wiki/Chaos_theory
Wikipedia on chaos theory. The Chaos Hypertextbook linked at
hypertextbook.com/chaos/, up to the
section on strange attractors, seems a reasonable
followup. You needn't be a mathematician, but need to be
happy with multidimensional real functions.
www.wolframscience.com/reference/notes/971c
Stephen Wolfram's history of chaos theory, up to
James Gleick's popular-science book Chaos.
projecteuclid.org/Dienst/UI/1.0/Summarize/euclid.ss/1032209661
David L. Banks
A conversation with I. J. Good, by David Banks,
Statistical Science, Volume 11, Number 1, 1996.
"The Perceptron, and a 1949 book by the psychologist
Donald Hebb, provoked me to write an article
called
'Speculations Concerning the First Ultraintelligent
Machine,' based on the concept of artificial
neural networks and what I called a subassembly
theory of the mind. I thought neural networks, with
their ultraparallel working, were as likely as programming
to lead to an intelligent machine, but
brains use both methods; they have parallel architecture
and also use language and reasoning. So
we can learn from our brains as well as with them.
When discussing complex systems, like brains and
other societies, it is easy to oversimplify: I call
this Occam's lobotomy. Evolution is opportunist; it
doesn't have to choose when a compromise works
better."
ei.cs.vt.edu/~history/Good.html
Biography of I. J. Good, by A. N. Lee, 1994. This describes him as
the "Overlooked Father of Computation". Overlooked because
of the secrecy surrounding his work at Bletchley Park.
Good featured, together with Minsky, in Arthur C. Clarke's, in 2001, a Space Odyssey (1968).
According to the above biography, this contains the quote:
"In the 1980's,
[Marvin] Minsky and [Jack] Good had shown how neural
networks could be generated automatically - self replicated - in
accordance with any arbitrary learning program. Artificial brains
could be grown by a process strikingly analogous to the
development of a human brain."
www.cyberlife-research.com/people/steve/
Grand's home page at Cyberlife, describing the origins of the evolving
neural-net driven animats in
his game "Creatures".
www.gamewaredevelopment.co.uk/creatures.php?id=C0_8_6
The history of "Creatures" by Creature Labs, now a subsidiary of Gameware.
fp.cyberlifersrch.plus.com/articles/ieee9.pdf
Moving AI Out of its Infancy:
Changing Our Preconceptions,
IEEE Intelligent Systems,
November/December 2004.
Grand talks about his work on the robot orang-utan Lucy:
"The other day, it was my turn to answer stupid questions
about the movie I, Robot. 'Do you think it's
about time we started incorporating
Asimov's three laws
into
real robots?' a journalist asked. I replied that Asimov's laws
are about as relevant to real robotics as leechcraft is to modern
medicine. Yes, before anyone writes me smug emails, I
know that leeches are very useful in modern medicine,
but I said 'leechcraft.' Leeches might be useful, but the paradigm
of thought that originally led to their use is a ridiculous
anachronism.
The same is true for Asimov's laws."
www.akri.org/ai/steveg.htm
Artificial Intelligence : Steve Grand "Machines Like Us".
Transcript from Grand's presentation at Applied
Knowledge Research and Innovation's Biennial Seminar on 17th October 2002.
"Anyway what went wrong with A.I.? Well its all this guy's fault and
I presume most of you recognise Alan Turing."
www.salon.com/books/int/2002/01/02/grand/?CP=COR&DN=310
The emotional machine, by Suzy Hansen,
Salon, 2nd January, 2002.
"Steve Grand, designer of the artificial
life program Creatures, talks about the stupidity of computers, the role of desire
in intelligence and the coming revolution in what it means to be 'alive.'"
www.unites.uqam.ca/cnc/en/profs/harnad.htm -
Harnad's home page.
www.ecs.soton.ac.uk/~harnad/Hypermail/Foundations.Cognitive.Science2001/0158.html
Immediate future of AI, a
newsgroup discussion with a reporter for
Smart Business Magazine, 28th July 2001.
Harnad writes about where AI went wrong, and on
how robotics has
made its way to centre-stage: as a way to "ground" the symbols
that
John Searle's
Chinese Room inhabitant merely
shuffles without understanding.
The mail links to several Harnad publications, including
his classic
The
Symbol Grounding
Problem.
www.harryharrison.com/ -
Harrison's home page.
members.aol.com/dmchess/www/turing.html
Harrison is a well-known science-fiction writer. Less well-known is that he
co-authored a book with
Marvin Minsky. The Turing Option, 1993,
is about the inventor of a new AI who is shot through the brain,
destroying crucial neural connections. But, using advanced AI
techniques based upon Minsky's Society of Mind (and, I believe,
expert systems and Lenat's Cyc), his brain is
repaired and his memories restored. This link reviews the book.
web.media.mit.edu/~minsky/papers/option.chapters.txt
Two unpublished chapters of The Turing Option, on Minsky's site.
web.media.mit.edu/~push/ExaminingSOM.html
Examining the Society of Mind, by
Push Singh, MIT,
October 2003.
The author looks at some of the AI history behind Society of Mind, breaks
the theory down into its component ideas, and examines some implementation
problems.
www.ecs.soton.ac.uk/~harnad/Archive/hebb.html
D. O. Hebb.
Father of Cognitive Psychobiology
1904-1985, by
Stevan Harnad, 1985.
Harnad's personal recollection and appreciation of Hebb:
"But then Hebb reminded us of the problem anew,
first through suggestive accounts of his work
with Penfield on the localization of memories in the
brain, and then from the viewpoint of his own specific
hypothesis that thoughts could actually be the activity of
reverberating circuits of neurons called 'cell-assemblies.'
I don't think his idea had its full impact on me at the moment
he described it. Rather, it was after the lecture, as I thought
about it, and thought that my thoughts may well consist of those
physical things I was thinking about, that I realized what a
radically different world view such a theory represented, and
that it all had a ring of reality to it that made the Freudian
notions I had been flirting with sound like silly fairy tales.
Here were the real unconscious processes underlying our thinking,
instead of the anthropomorphic machinations of some Freudian
'unconscious mind,' which now began to look rather like a
supernumerary and supererogatory alter
homunculus:
One
mind/body problem was enough!"
psychclassics.yorku.ca/Hebb/
Drives and the C.N.S. (Conceptual Nervous System),
Psychological Review, Volume 62, 1955.
Online at Christopher D. Green's
Classics in the History of Psychology:
"The problem of motivation of course lies close to the heart of the
general problem of understanding behavior, yet it sometimes seems the
least realistically treated topic in the literature. In great part, the
difficulty concerns that c.n.s., or "conceptual nervous system," which Skinner
disavowed and from
whose influence he and others have tried to escape. But the conceptual
nervous system of 1930 was evidently like the gin that was being drunk
about the same time; it was homemade and none too good, as Skinner pointed out,
but it was also habit-forming; and the effort to escape has not really been successful.
Prohibition is long past. If we must drink we can now get better liquor; likewise,
the conceptual nervous system of 1930 is out of date and - if we must neurologize -
let us use the best brand of neurology we can find.
Though I personally favor both alcohol and neurologizing, in moderation,
the point here does not assume that either is a good thing. The point is
that psychology is intoxicating itself with a worse brand than it need use.
Many psychologists do not think in terms of neural anatomy; but merely
adhering to certain classical frameworks shows the limiting effect of earlier neurologizing."
www.cs.umd.edu/~hendler/ -
Hendler's home page.
www.cnn.com/chat/transcripts/1999/12/hendler/index.html
A chat about the future of artificial intelligence,
from CNN's @2000 chat series, January 1, 2000.
Did you know Microsoft's paperclip used
Bayesian belief networks? Hendler
answers audience questions about AI.
www.cs.umd.edu/users/hendler/funding-talk/
How to get that first grant:♂A young
scientist's guide to (AI) funding in America.
Slides from a tutorial presented at the Fifteenth National
Conference on Artificial Intelligence (AAAI98), July 1998.
www.cs.toronto.edu/~hinton/ -
Hinton's home page.
www.cs.toronto.edu/~hinton/talks/gentle.ppt
A "very gentle after-dinner version" of Hinton's IJCAI-2005 Research Excellence Award Lecture
Can computer simulations of the brain allow us to see into the mind?.
www.cs.toronto.edu/~hinton/absps/connectionist.pdf
Preface to the special issue on connectionist symbol processing,
Artificial Intelligence, Volume 46, 1990.
www.cs.rhul.ac.uk/NCS/vol1_3.pdf
A Brief History of Connectionism by
David A. Medler,
Neural Computing Surveys, Volume 1, 1998.
A detailed history of connectionism in cognitive
science. It mentions the 1981 book
Parallel Models of Associative Memory by Hinton and
J. A. Anderson, saying that in many ways, this
book acts as a bridge between the "Old Connectionism" of the
Perceptron and the "New Connectionism" of fully-trainable and
computationally powerful networks.
www.cogs.indiana.edu/people/homepages/hofstadter.html -
Hofstadter's home page.
www.stanford.edu/group/SHR/4-2/text/hofstadter.html
on seeing A's and seeing As, from
Constructions of the Mind:
Artificial Intelligence and the Humanities.
Volume 4, Issue 2 of Stanford Humanities Review, 1995.
Hofstadter argues that logic-based AI may have
reached a dead-end, being brittle and too little concerned with
perception. But, in contrast to some researchers' views of it,
perception is itself a highly abstract act - even a
highly abstract art - in which intuitive guesswork and subtle judgments play
starring roles. He illustrates with pictures of
Bongard pattern-recognition problems, and concludes:
"As Heinz Pagels reports in his book The Dreams of Reason,
one time
[the mathematician Stanislaw] Ulam and his mathematician friend Gian-Carlo Rota
were having a lively debate about artificial intelligence, a
discipline whose approach Ulam thought was simplistic. Convinced
that perception is the key to intelligence, Ulam was trying to explain
the subtlety of human perception by showing how subjective it is, how
influenced by context. He said to Rota, 'When you perceive intelligently,
you always perceive a function, never an object in the physical sense.
Cameras always register objects, but human perception is always the
perception of functional roles. The two processes could not be more
different.... Your friends in AI are now beginning to trumpet the role
of contexts, but they are not practicing their lesson.
They still want to build machines that see by imitating cameras, perhaps with some
feedback thrown in. Such an approach is bound to fail...'"
www.sciencedaily.com/releases/2003/02/030214075837.htm
Falling Prey To Machines?
Adapted from a news release issued by University Of Michigan College Of Engineering,
ScienceDaily, 14th February 2003:
"For Holland, the crucial leap in machine
intelligence will be when computers start thinking like human beings,
rather than just reaching the same results as them with different
processes. This kind of advanced artificial intelligence
would involve learning new skills, adapting to unforeseen
circumstances and using analogy and metaphor like humans do. To
make these breakthroughs possible, researchers will need an
overarching theory that can shape the field of artificial
intelligence in the same way that
Maxwell's theory of electromagnetism shaped modern physics."
www.inf.ed.ac.uk/people/staff/James_Howe.html -
Howe's home page.
www.dai.ed.ac.uk/AI_at_Edinburgh_perspective.html
Artificial Intelligence at Edinburgh University : a Perspective,
1994.
And a history.
www.compapp.dcu.ie/~humphrys/ -
Humphrys's home page.
www.compapp.dcu.ie/~humphrys/philosophy.html
AI is possible .. but AI won't happen:
The future of Artificial Intelligence.
Talk given at the "Next Generation" symposium, the
"Science and the Human Dimension" series, Jesus College
Cambridge, August 1997.
In this and a later talk (The Hardest Problem in the History of Science,
www.compapp.dcu.ie/~humphrys/ica.html, 2000),
Humphreys claims that although possible in theory, AI is impossible in
practice. One reason: we can't expect to get anywhere by building a
single isolated Artificial
Intelligence
alone in the lab; our AIs must have the opportunity to
engage in repeated social interactions and evolve
a rich culture.
www.smalltalk.org/smalltalk/TheEarlyHistoryOfSmalltalk_TOC.html
The Early History of Smalltalk, 1993:
"I will try to show where most of the influences
came from and how they were transformed in the
magnetic field formed by the new personal computing metaphor.
It was the attitudes as well as the great ideas of the pioneers
that helped Smalltalk get invented. Many of the people
I admired most at this time - such as Ivan Sutherland,
Marvin Minsky,
Seymour Papert,
Gordon Moore,
Bob Barton,
Dave Evans,
Butler Lampson,
Jerome Bruner, and others - seemed to have a splendid sense that their
creations, though wonderful by relative standards, were not near to
the absolute thresholds that had to be crossed. Small minds try to form religions,
the great ones just want better routes up the mountain."
people.cs.uchicago.edu/~mark/51050/lectures/lecture.4/lecture.4.pdf
There's a nice anecdote by Kay recalled in J. Mark Shacklette's lecture notes linked
here on
object-oriented programming:
"One little incident of LISP beauty happened when
Allen Newell visited PARC
with his theory of hierarchical thinking and was challenged to prove it. He
was given a programming problem to solve . . . given a list of items, produce
a list consisting of all the odd indexed items followed by all of the even
indexed items. [Newell] got into quite a struggle to do the program [with his
IPL-V like language]. In 2 seconds I wrote down oddsEvens(x) =
append(odds(x), evens(x)). This characteristic of writing down many
solutions in declarative form and have them also be the programs is part of
the appeal and beauty of this kind of language. Watching a famous guy
much smarter then I struggle for more than 30 minutes to not quite solve the
problem his way (there was a bug) made quite an impression."
www.doc.ic.ac.uk/~rak/ -
Kowalski's home page.
www.doc.ic.ac.uk/~rak/history.html
Robert Kowalski: A Short Story of My Life and Work,
April 2002.
Kowalski's memories of school, Stanford, logic,
computing, and the heady days
of Prolog working with
Alain Colmerauer and others.
On arriving
at Edinburgh University
Meta-mathematics Unit, and seeing the sign 'Department of Computer Science':
"My
heart sank. I hated computers, but I decided I would
stick it out, get my PhD as quickly as possible, and resume my search for truth."
He describes how he
helped develop microProlog for schools, working with
Frank McCabe and
Richard Ennals.
Three years later, he became the most
senior academic in Britain to argue the logic programming case
for Britain's response to the
Japanese Fifth Generation Project:
"It was chaos. Academics argued with academics, industrialists with both
academics and fellow industrialists - all presided over by the British civil service.
We all wanted to carve out a slice of the action for ourselves. Some of us went
further by arguing that we should follow the lead of the Fifth Generation Project and focus on
logic programming to the detriment of other areas. That was a big mistake."
www.kurzweilai.net/ -
Kurzweil's KurzweilAI.net page.
"The Singularity is near"!
www.guardian.co.uk/science/story/0,,1647150,00.html
The ideas interview: Ray Kurzweil ,
Guardian,
21st November, 2005.
"'By 2020, $1,000 (£581) worth of computer will equal the processing power of the
human brain,' he says. 'By the late 2020s, we'll have reverse-engineered human brains.'"
zooland.alife.org/
What is Artificial Life?, Zooland site.
psychclassics.yorku.ca/Lashley/neural.htm
Basic Neural Mechanisms in Behavior,
Psychological Review, Volume 37, 1930.
Online at Christopher D. Green's
Classics in the History of Psychology.
"Among the systems and points of view which comprise our efforts to formulate a
science of psychology, the proposition upon which there seems to be most nearly a
general agreement is that the final explanation of behavior or of mental processes is to
be sought in the physiological activity of the body and, in particular, in the properties of the
nervous system. The tendency to seek all causal relations of behavior in brain processes
is characteristic of the recent development of psychology in America. Most of our text-books
begin with an exposition of the structure of the brain and imply that this lays a foundation
for a later understanding of behavior. It is rare that a discussion of any psychological problem
avoids some reference to the neural substratum, and the development of elaborate neurological
theories to 'explain' the phenomena in every field of psychology is becoming increasingly fashionable.
In reading this literature I have been impressed chiefly by its futility. The chapter
on the nervous system seems to provide an excuse for pictures in an otherwise dry and
monotonous text. That it has any other function is not clear; there may be cursory
references to it in later chapters on instinct and habit, but where the problems of
psychology become complex and interesting, the nervous system is dispensed with."
www.cyc.com/cyc/company/lenat -
Lenat's home page.
www.cyc.com/cyc/technology/halslegacy.html
From 2001 to 2001: Common Sense and the Mind of HAL, in
Hal's Legacy:
2001's Computer as Dream and Reality, edited by
David Stork, 2001.
Lenat explains how to build HAL in three easy steps:
- Prime the pump with the millions of everyday terms,
concepts, facts, and rules of thumb that comprise human consensus reality - that
is, common sense.
-
On top of this base, construct the ability to communicate in a
natural language, such as English. Let the HAL-to-be use that ability to vastly enlarge its knowledge base.
-
Eventually, as it reaches the frontier of human knowledge in some
area, there will be no one left to talk to about it, so it will need
to perform experiments to make further headway in that area.
www.ainewsletter.com/newsletters/aix_0501.htm#l
My January 2005 entry on Lenat, including links concerning his common-sense
reasoning project Cyc which will supply these
millions of everyday terms,
concepts, facts, and rules of thumb.
www.ainewsletter.com/newsletters/aix_0501.htm#o
My January 2005 entry on OpenCyc, the open-source
version of Cyc.
www.cse.ucsc.edu/personnel/faculty/levinson.html -
Levinson's home page.
www.ucsc.edu/oncampus/currents/97-05-05/chess.htm
"Deep Blue" inspires deep thinking about artificial intelligence by computer scientist, by
Robert Irion, 5th May, 1997.
Levinson criticises Deep Blue for its lack of meta-reasoning and learning:
"'Deep Blue is a powerful entity, and it represents a wonderful engineering effort,'
Levinson said this week as he looked forward to following the games live on the Internet.
'I do agree that it sits somewhere on the scale of ''intelligence.'' But even if it proves the
most successful approach toward beating the world champion in chess, it's a long
way from artificial intelligence. What it really lacks is autonomy and adaptability.'"
satirist.org/learn-game/projects/morph.html
Levinson's Morph project, his learning chess program which
the feature contrasts with Deep Blue.
www-formal.stanford.edu/jmc/reviews/lighthill/lighthill.html
Review of "Artificial Intelligence: A General Survey", by
John McCarthy, 1973 or 1974.
Lighthill was commissioned by the
British Science Research Council, the main funding body for university
research, to write a report which would help them
decide on future requests for funding.
The report criticised a lot of AI research, and
many believe it was responsible for
the large cuts in funding that took place after 1973,
causing researchers to leave for the U.S.,
and a British "AI Winter" that lasted until
the expert systems boom and the response to the
Fifth Generation
project in the early 1980s. Here, McCarthy
reviews the report; while he finds fault
with Lighthill's approach to AI,
he also identifies faults
in AI research itself, including the
"look ma, no hands" disease.
www-formal.stanford.edu/jmc/reviews/bloomfield/bloomfield.html
The Question of Artificial Intelligence, by
John McCarthy, 2000:
"We make a final remark about the Lighthill report...
When a physicist is forced to think about AI he
generally reinvents the subject in his individual way.
Some expect it to be easy and others impossible. Lighthill was in
the latter category. In the 1974 BBC debate, I thought I had a
powerful argument and asked Lighthill why, if the physicists
hadn't mastered turbulence in 100 years, they should expect
AI researchers to give up just because they hadn't mastered AI in
20. Lighthill's reply, which BBC unfortunately
didn't include in the broadcast, was that the
physicists should give up on turbulence. Hardly any physicists
would agree with Lighthill's statement, and maybe he didn't mean it."
www-formal.stanford.edu/jmc/reviews/lighthill-20/lighthill-20.html
Lessons from the Lighthill Flap, by
John McCarthy:
"This is a review of Martin Lam's The Lighthill Report - 20 years after:
Martin Lam gives us a British civil servant's view of the Lighthill report and
subsequent developments. My comments concern some limitations of this view that may
be related to the background of the author - or maybe they're
just a scientist's prejudices about officials.
Lam accepts Lighthill's eccentric partition of AI research into Advanced
Automation, Computer-based Studies of the Central Nervous System and Bridges
in between. This classification wasn't accepted then and didn't become accepted
since, because it almost entirely omits the scientific basis of AI."
www.calresco.org/lucas/selforg.htm
Self-Organization and Human Robots,
International Journal for Advanced Robotic Systems, March 2005.
A speculative proposal to apply complexity, self-organisation and attractors to
robot design.
www.cs.unm.edu/~luger/ -
Luger's home page.
www.cs.unm.edu/~luger/ai-final/preface.html
This page links to the preface of Luger's book
Artificial Intelligence: Structures and Strategies for
Complex Problem Solving, now in its 5th edition. In his
preface, written in 2004, Luger talks about how earlier
editions have dated as AI developed. One change is that
stochastic methods such as Bayesian networks and Markov models
are much more important. More generally, the debate between
the
neats and the scruffies has given way to dozens of
other debates between diverse interests. This diversity is
to be welcomed:
"Our original image of AI as frontier science where outlaws,
prospectors, wild-eyed prairie prophets and other dreamers were being slowly
tamed by the disciplines of formalism and empiricism has given way to a
different metaphor: that of a large, chaotic but mostly peaceful city, where
orderly bourgeois
neighborhoods draw their vitality from diverse, chaotic, bohemian districts."
www.dai.ed.ac.uk/homes/cam/ -
Malcolm's home page.
www.dai.ed.ac.uk/homes/cam/WRRTW.shtml
Why Robots Won't Rule the World, 2000:
"This is a general resource page for arguments against the idea that
robots (or some other superintelligent machines) will supersede us as the
dominant 'life' form and take over the world from us. These arguments have
received a lot of publicity in the national press of many countries, on TV and
radio, and in popular science journals such as Scientific American. I'm surprised
that so many well-educated people take the ideas
seriously. Since they do, it is worth while explaining why these ideas are silly."
www.dai.ed.ac.uk/homes/cam/RWR_comments.shtml
Robots Won't Rule, 2000:
"It was rumoured in some of the UK national press of
the time [a bit more than 10 years after
Lighthill] that Margaret Thatcher watched Professor Fredkin
being interviewed on a late night TV science programme.
Fredkin explained that superintelligent machines were
destined to surpass the human race in intelligence quite
soon, and that if we were lucky they find human beings
interesting enough to keep us around as pets. The rumour is
that Margaret Thatcher decided on seeing that that the 'artificial intelligentsia' whom
she was just proposing to give lots of research funds under the
Alvey Initiative were
seriously deranged. Her answer was to double the amount of industrial support required by
a research project in order to be eligible for Alvey funding,
hoping thereby to counterbalance their deranged flights of fancy with industrial common sense."
kybele.psych.cornell.edu/~edelman/marr/marr.html
David Marr
a short biography,
International Encyclopaedia of Social and Behavioral Sciences, by
Shimon Edelman
and
Lucia M. Vaina, 2001:
"A consummation of this three-pronged effort to develop an
integrated mathematical-neurobiological understanding of the
brain would in any case have earned Marr a prominent place in a
gallery, spanning two and a half centuries (from John Locke to
Kenneth Craik), of British Empiricism, the epistemological stance
invariably most popular among neuroscientists. As it were, having
abandoned the high-theory road soon after the publication of the
hippocampus paper, Marr went on to make his major contribution to
the understanding of the brain by essentially inventing a field and a
mode of study: computational neuroscience. By 1972, the focus of his
thinking in theoretical neurobiology shifted away from abstract
theories of entire brain systems, following a realization that
without an understanding of specific tasks and mechanisms - the issues from which his earlier
theories were 'once removed' - any general theory would be glaringly incomplete."
www-formal.stanford.edu/jmc/ -
McCarthy's home page.
www-formal.stanford.edu/jmc/whatisai/whatisai.html
What is Artificial Intelligence?, 2004.
"This
article for the layman answers basic questions about artificial intelligence. The opinions expressed here
are not all consensus opinion among researchers in AI".
www-formal.stanford.edu/jmc/robotandbaby.html
The Robot and the Baby, 2004.
McCarthy's first science fiction story,
which partly illustrates his opinions about what household robots should be like. To be
contrasted with the film AI, of which
McCarthy notes in his intro that:
"There is no more of the science of AI in the movie than there
is in the Pinochio story of more than 100 years ago. One should also not take seriously any of the
ideas of the movie of what robots might really be like."
www-formal.stanford.edu/jmc/history/lisp/lisp.html
History of Lisp, 1979.
www-db.stanford.edu/pub/voy/museum/pictures/display/1-7.htm
"In my opinion, getting a language for expressing general
commonsense knowledge for inclusion in a general
database is the key problem of generality in AI."
A 1971 quote from McCarthy, visible in
one of the photos of the Stanford AI Lab pictured here.
www-formal.stanford.edu/jmc/mcc59/mcc59.html
Programs with Common Sense, 1959.
About McCarthy's Advice Taker program.
www-db.stanford.edu/pub/voy/museum.html
Tree (incomplete) of McCarthy's students,
from the
Stanford Computer History exhibits.
cs-www.cs.yale.edu/homes/dvm/ -
McDermott's home page.
wiki.alu.org/Drew_McDermott
McDermott's road to Lisp, via the assembly-like list-processing language
IPL-V.
From the Association of Lisp Users wiki:
"In the 1950s list processing seemed like a radical innovation in an array-oriented world."
(Herbert Simon talks briefly about using IPL-V
for the Logic Theorist
in his memories of
Allen Newell, which I've linked from that section.)
www.acm.org/crossroads/xrds3-1/interview.html
An Interview with
Drew McDermott,
by Kentaro Toyama, ACM Crossroads, 1996:
"Q: Do you think there are advances in other fields that might propel AI forward?"
"A: When I was in grad school, there was a tendency to believe AI was a paradigm
competing with other paradigms. So we would say, we're not going to use
Kalman filters [from engineering], we'll use AI. Nowadays, AI
simply absorbs those techniques. Those techniques
will continue to be of great importance. Anything at all
that might be considered a part of a
theory of control of an organism would be used by AI."
www.asa3.org/ASA/topics/PsychologyNeuroscience/PSCF3-92Thorson.html
An I Behind the Eye: Donald MacKay's Gifford Lectures,
by W. R. Thorson. Perspectives on
Science and Christian Faith, Volume 44, March 1992.
This essay is a review of Donald MacKay's
Behind the Eye, edited by
Valerie MacKay, 1991. The book originated with MacKay's
1986 Gifford Lectures in Natural Theology, and
relates cognitive science - connectionism included - to
Christian belief, spirituality,
death, and a hereafter.
www.peterjblackburn.com/sermons/pb990620.htm
Responding to the Word, Peter J. Blackburn, 1999.
Sermon concerning Christianity in a Mechanistic Universe and other essays, edited by Donald M. MacKay, 1965:
"A number of years ago, Donald M. MacKay, then Professor of Communication at
the University of Keele, wrote an article in which he was discussing
the relationship between faith and science. In the course of the article
he describes what he calls 'the fallacy of nothing buttery.' The phrase
catches the attention and lodges in the memory - but has nothing to do with the kitchen or dining table.
He was trying to highlight the danger of assuming that, because we grasp some of the truth, we therefore know all the truth -
in particular, the inference that the spiritual dimension can be ruled out because of our insights into the
physical world, the tendency to say that reality is 'nothing but' the physical world."
www.aiai.ed.ac.uk/~dm/dm.html -
Michie's home page.
www.aiai.ed.ac.uk/events/ccs2002/CCS-early-british-ai-dmichie.pdf
Recollections of early AI in Britain: 1942-1965. Transcript of the video for the
BCS Computer Conservation Society's October 2002
Conference on the history of AI in Britain.
Michie's life in AI, from friendships with Turing and
Good at
Bletchley Park, up to the
Edinburgh project on FREDERICK -
"Friendly Robot for Education, Discussion and
Entertainment, the Retrieval of Information and the Collation of
Knowledge".
www.doc.ic.ac.uk/~shm/MI/Michie.ps
The "Machine Intelligence" series,
a note "prepared in response to a suggestion made at
the recent York meeting of the new MI Board".
Michie writes about the requirements for maintaining this series, and the boldness needed to start it:
"Identifying and fostering new departures demands a correspondingly
radical editorial style. Paradigm-spotting in science is in spirit closer to
maritime exploration than it is to the administration of the settled
landfalls that follow. Atypically in human affairs boldness is all, both in
new sightings and in immediate follow-up. With equal boldness,
editorial leadership must select contributors and themes for each new
Workshop on one single criterion: are they likely to engender the
proliferation of influential novelty?
In this spirit the first Machine Intelligence Workshop was convened in
1965. That year had seen a potential revolution in mechanizable aids to
reasoning. Thanks to the vigilance of the young
Rod Burstall, it was
instantly spotted and given prominence in this first volume, namely
Robinson's resolution principle."
George A. Miller
wordnet.princeton.edu/~geo/ -
Miller's home page.
www.cogsci.princeton.edu/~geo/Miller.pdf
The cognitive revolution:
a historical perspective,
Trends in Cognitive Sciences Volume 7, Number 3, March 2003:
"Cognitive science is a child of the 1950s, the product of
a time when psychology, anthropology and linguistics
were redefining themselves and computer science and
neuroscience as disciplines were coming into existence.
Psychology could not participate in the cognitive
revolution until it had freed itself from behaviorism,
thus restoring cognition to scientific respectability. By
then, it was becoming clear in several disciplines that
the solution to some of their problems depended crucially
on solving problems traditionally allocated to
other disciplines. Collaboration was called for: this is a
personal account of how it came about."
www.well.com/user/smalin/miller.html
The Magical Number Seven, Plus or Minus Two: Some Limits on Our
Capacity for Processing Information,
The Psychological Review, Volume 63, 1956.
web.media.mit.edu/~minsky/ -
Minsky's home page.
www.wired.com/news/technology/0,1282,58714,00.html
AI Founder Blasts Modern Research,
by Mark Baard,
Wired, 13 May 2003.
"'AI has been brain-dead since the 1970s,' said
AI guru Marvin Minsky in a recent speech at Boston University.
Minsky co-founded the MIT
Artificial Intelligence Laboratory in 1959 with John McCarthy."
Disagreement between Minsky and
