Pollack has worked on Artificial Intelligence using
computers since 1975. In 1987, he received a Ph. D.
in Computer Science from the University of Illinois.
He is now a professor at Brandeis University, where
he is Director of the Dynamical and Evolutionary Machine
Organization, known as the DEMO
Laboratory . A prolific scientist, inventor and
entrepreneur, Dr. Pollack has made a few significant
contributions to the fields of Artificial Intelligence
and Artificial Life. Through his work on machine learning,
neural networks, evolutionary computation and dynamical
systems, Pollack has sought to understand the processes
by which systems can self-organize and develop complex
and cognitive behaviors. At DEMO, Pollack and his colleagues
have applied "co-evolutionary learning" to significant
problems in game playing, problem solving, search, language
induction, robotics, and even educational learning across
links to this scientist's home page and other related infomation
please see our resources
Kevin Labeau asked:
What is the time period involved in the computer selecting
a tangible working model to its fruition? In other words,
how long does the computer take to make a working model
in situ and then become reality?
lose patience after a couple of days! But as computers
get faster, they evolve more stuff in less time, so
now a run may take a couple of hours. Next year it might
take minutes. The rapid prototyping machine takes almost
a day to fabricate the bodies, but there are faster
machines on the horizon. As an example, laser printers
used to take a minute per page, and now can spit out
30 a minute.
key thing is not the manufacturing mechanism but the
constraint on what we are automatically designing so
it can be built and that it can work in the real world.
We expect that with the right assembly systems we can
remove the human element completely for certain classes
Mark Dreisbach asked:
I really enjoyed the most recent program on PBS. I sat
in wonderment as the computer was able to actually "learn"
the best method for satisfying the question at hand.
As the father of twin boys, I was wondering if any of
the print outs of the Lego models would be available
or a list of the particular Lego parts is listed somewhere
so we might attempt to build some of your designs and
put them into practice? It would be a much better use
of the 1000+ Legos hanging around the house that I seem
to step on in the middle of the night.
the computer didn't learn the "best" way, it just gets
better over time until either it stops making progress
or a human gets bored waiting. We do have blueprints,
but they are big things printed out on a HP plotter.
You can play with Lego evolution from a web browser,
on our lab's
homepage, but we don't have an economical way to
deliver plots to people.
I want to follow up on Alda's remark that these toy-like
creatures could be the forebears of a race of super-robots
which wipe out humanity. How are your robots going to
follow Asimov's 3 Laws? I'm surprised PBS didn't discuss
Bill Joy's warnings about self-replicating robots in
the context of the show. Shouldn't we be really afraid?
the story was about automatic design and production
of fax machines, it might not seem so scary. Vending
Machines, automatic teller machines and inkjet printers
are robots by my definition: computer software in control
of some kind of real physical machine, working 24 hours
a day, moving people into other jobs. Few people want
to deal with human soda vendors or to return to the
days of waiting in line for 9-5 banking.
Now, if you stick your finger in a $99 inkjet printer,
you will be pinched and sprayed with ink, and then it
will probably break and cost more than $99 to repair.
This robot has no conception of a human, little awareness
of anything, except if a button is pushed, a piece of
paper is loaded and where the printhead is. It has taken
the industry 12 years to make printers aware of how
much ink is left. It will be hundreds of years before
an inkjet printer can be instructed in law.
Robots are not general purpose, but special purpose,
and even though humans can build lovely machines, they
end up being way too expensive for the limited work
they can do. The high cost of robot design can only
be recovered through mass production or in very high
margin industries like software and pharmaceuticals.
is of theoretical interest only, and has been studied
for a long time, following von Neumann's work on cellular
automata. We know how to do it in pure software. Until
the day of artificial persons, who can work a machine
shop, program a computer, order, arrange, and install
the chips and motors, in their own babies, the danger
is minimal. No Electro-Mechanical (EM) robot will be
able to eat an old computer or fax machine to get parts
for its children, because it needs highly integrated
specific parts. To gain control of the means of production
for an out-of-control take-over-the-world scenario a
robot would need to buy General Electric, and replace
all the people with computers.
I do not mean to sound facetious, because I have thought
a lot about the problems. Software robots which replicate
themselves, like the "love bug" Microsoft Outlook Virus,
are a real threat. And nobody is considering whether
all the computing power inside Cisco and Sycamore routers
and switches of the Internet can mutate into an evil
brain. I proposed to the government one day to set up
a "Search for Extra-Terrestrial Intelligence" project,
only to watch for signs of life and intelligence arising
in telecommunications network dynamics.
real issue for robotics is not an out of control self-replication
problem, but whether humanity is aware of the mistakes
of the past, where the power plant, the paper plant,
and the automobile externalized costs and polluted the
I worry about robots which get energy from internal
combustion or by eating organic lifeforms - commercial
success leads to less air to breathe or food to eat.
I worry about the cyborgization of animals and humans
for commercial or military purposes, such that in a
war, all the local animals are executed first. I worry
whether robots which can perform hazardous duties enable
humanity to engage in even more hazardous activities.
I worry about the effect of hybrid human/robot immortality
on the tenure system.
James Lee asked:
I have many difficulties with the theory of evolution
in regards to animal and plant species. I don't understand
why it is still referred to as a theory when it doesn't
satisfy the basic rules of theories. Is the idea of
theory being warped to fit biological evolution? I realize
that your work doesn't directly approach the application
of theories to animals etc., but I thought you may be
able to comment on this problem.
are right that evolution is not a theory. It is a framework,
a set of principles for understanding how life emerged
from non-life, and how life continues to change over
time. And all evidence suggests that these are the correct,
if incomplete, principles. You need a framework to ask
questions scientifically, such that careful observation
and experimentation lead to increased perception of
the truth of the universe. If the framework does not
allow questions to be asked, it is ultimately unproductive.
I think that there are many times where science reaches
a dead end, and people are left with strong - almost
religious - convictions but no evidence, and no means
to collect it. A lot of areas of cognitive science,
for example, have frameworks which initially seemed
productive, but when pushed, left hard questions as
magic to be answered by another field. I can think of
three: AI theories which required solutions to combinatorial
problems, waiting for a solution to the fundamental
conundrum of computer science (does P=NP?), language
acquisition theories which presume but can never know
the child's biological endowment, and theories of the
historical stages of consciousness which cannot be tested
without a time machine.
while my lab's work doesn't bear on animals and plants
per se, it does focus on the principles which one day
may allow software to self-organize the same way as
the matter, energy, and information processes we call
"life". And we don't care what actually happened, or
what actually exists, but only care about the process
by which it came to be. Darwin is mostly right, but
he did not really understand computation, dynamical
systems, and game theory, because they were not developed
in his day.
Paul Aspenson asked:
How do you explain the 2nd Law of Thermodynamics when
you place this law beside your theories in evolution
and natural selection?
is a great question. In my opinion, the best definition
of life is that it is a process, far from equilibrium,
which wastes energy and creates structures - a local
reversal of entropy. How can any system act to reverse
entropy when it seems to violate the second law? The
answer is that the system is open - it wasting energy
given from outside. We are trying to formalize and understand
this well enough that a piece of software can waste
a bunch of computer cycles and create more and more
can see already how computer time is turned into knowledge,
by considering a traditional game playing program with
an evaluation function which estimates the goodness
of any position - as it searches the tree of moves deeper
and deeper, its evaluation of a board position gets
better and better - in the limit, it can search all
the way to the final move of a game. This basic law
of AI - the knowledge-search tradeoff - is how Deep
Blue beat Kasparov. Chess knowledge was formed by massive
wasting of computer time using custom IBM hardware.
often get caught up with definitions of evolution which
involve sex, reproduction, survival of the fittest,
animals, and so on, and obscure the underlying thermodynamic
question. In our view, species, individuals, lifetimes,
biological-truth-as-it-is are just arbitrary side-effects
of the anti-entropic process as happened in one "run"
of organic chemistry on earth. And it has run so long
that it is an extreme waste of time to try to reverse
engineer it. We are faced with Brains, Minds, Species,
Languages, and Ecosystems, most of which are arbitrary
accidents built on top of arbitrary accidents selected
for a billion years.
Once such a local entropy reversal reaction is going,
and there is sufficient energy to dissipate, the structures
which support more and more complexification must emerge
as a mathematical consequence. In other words, dissipate
energy, create knowledge.
Our notion of complexity and knowledge is disputed.
Kolmogorov said that the complexity of a string is just
the smallest program which can generate it, leading
to the conclusion that random strings are the most complex.
But he didn't calculate the amount of energy dissipated
in the generation. Bennet's Logical Depth and Atlan's
Sophistication are more interesting measures for me
because they take computer time into account.
my lab we have started self-learning programs in game
playing, optimization, language, problem-solving, design,
and robotics, and each one teaches us a little more
about the missing principles - which are more about
the learning environment than the learning algorithm.
I've moved from one field of AI to another for 25 years,
and co-evolutionary learning is the first approach which
I have not been able to dismiss after a few years of
work. The ultimate goal is an open-ended computationally
universal chain-reaction of self-organization - or at
least being able to define what it is and isn't.