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| Foresight Update 9 - Table of Contents |
A publication of the Foresight Institute
 Foresight Update 9 - Table of
Contents | Page1 | Page2 | Page3 | Page4 | Page5 |
Evolutionary
EconomicsOn April 23-24, the Center for the Study of Market Processes
in conjunction with the Washington Evolutionary Systems Society
held a conference entitled "Evolutionary Economics: Learning
from Computation." An outgrowth of the Center's Agorics
Project, the conference explored the overlap among evolutionary
economics, computer modeling of complex evolving systems, and
machine learning.
Our first speaker was Peter M. Allen of the International
Ecotechnology Research Center in England. Allen described the
complex, non-linear, dynamic interrelationships between economic,
environmental, and cultural factors. Using computer models of the
Nova Scotian shelf fisheries that ran as he spoke, Allen
demonstrated that it is the non-average detail of time and place
which drives evolution, and that there can be no equilibrium in a
dynamic economy.
John H. Miller of the Santa Fe
Institute spoke on classifier systems and genetic algorithms.
These evolutionary machine learning techniques incorporate a
feedback system by which they adjust to success or failure. The
feedback system is based on economic principles: in classifiers,
for example, successful rules essentially "pay" other
rules for useful information.
Paul Werbos of the National Science Foundation spoke on neural
networks, another machine learning technique incorporating
economic principles. With neural networks, as with classifier
systems, there is a kind of payment back through the system by
which success is rewarded and the system evolves.
Mark S. Miller,
chief architect of the Xanadu Operating Company in Palo Alto,
California, spoke on Agoric Open Systems,
a logical next step in the evolution of computational systems
from closed and centrally controlled to open and evolving. Miller
discussed computational processes built on analogs to market
principles of property rights and competitive bidding (e.g.
for processor time and space in core main memory). Such processes
allow for greater complexity and efficiency in computer systems.
Other important guests were Robert W. Crosby of the Washington
Evolutionary Systems Society, who helped organize the conference,
and Jack Corliss of the Computer Systems Research Facility at
Goddard Space Flight Center, who showed a startling videotape of
complex evolutionary dynamics.
The conference made clear that examining the characteristics of
these various methodologies can help us better understand
economic processes. It also suggested possible applications of
these various methods that may help us build a more integrative
approach to economic problems.
Howard Baetjer is a PhD candidate at the George Mason
University Department of Economics. He is a member of the Agorics
Project, directed by Prof. Don Lavoie. This article is reprinted
from the newsletter @UX{Praxis}. The Project may be contacted at
the Center for the Study of Market Processes, phone 703-323-3483,
fax 703-764-6323. For papers on Agorics, see the Japan Prize article
below.
| Foresight Update 9 - Table of
Contents |
Minsky
Wins Japan PrizeThis year's Japan Prize (the Nobel Prize might be termed the
"Sweden Prize") was awarded to Marvin
Minsky of MIT for his pioneering work in artificial
intelligence. It includes $318,000 and a meeting with Emperor
Akihito. Minsky, now a professor at MIT's Media Lab, founded the
MIT Artificial Intelligence Lab and serves on the Foresight
Institute Board of Advisors.
In other foresighted news from Japan, their new International
Institute for Novel Computing will have twelve subcommittees to
study areas of future computing. Three of these are of particular
interest to FI members:
For computing news from both the U.S. and Japan, with a strong focus on neural computing, a good source is the newsletter Intelligence, edited by Edward Rosenfeld. While it is expensive ($295 in North America, $350 outside), it has the latest news on neural computing and we find it of great value. The publication has been coming out for six years so it seems likely to last. A typical issue is 8 pages, published monthly. They can be reached at PO Box 20008, New York, NY 10025, or by phone 212-222-1123 or 800-NEURALS.
| Foresight Update 9 - Table of
Contents |
OTA
Position AvailableThe Office of Technology Assessment in Washington, DC, is
beginning a study of the enabling technologies leading to
nanotechnology. These will include bottom-up approaches such as
STMs, bioengineering, and synthetic chemistry as well as top-down
approaches such as lithography. They are grouping these topics
under the general term 'miniaturization.'
They are seeking applicants for an 8-10 month interim position to
study these areas. The ideal candidate would be a recent PhD in
physics or engineering, but perhaps others would be considered,
since no one candidate will already be knowledgeable in such a
wide range of fields. Having completed the degree may not be
strictly necessary. OTA plans to make a decision and have the
candidate begin 'as soon as possible.'
This is a unique opportunity for a researcher to broaden his or
her technical background and have an influence on U.S. technology
policy. OTA will be presenting their results in a report to
Congress.
If you know of a potential candidate, have him or her send a
resumé to:
Dr. James Curlin
Program Manager
Communication and Information Technologies
Office of Technology Assessment
Washington, DC 20510-8025
202-228-6760
| Foresight Update 9 - Table of
Contents |
Wish
ListThe translators requested in the last issue have
volunteered--see Thanks column--but we could use more translators
from Japanese to English, especially those willing to do long
pieces. The translations usually are not time critical and can be
done over a few weeks. We would also appreciate additional
volunteer help in Macintosh desktop publishing, especially
layout.
FI needs equipment, new or used: a small photocopier, two fax
machines, and a second Laserwriter printer. Note that donations
of equipment or funds are tax-deductible as charitable
contributions.
If you or your company can help, call our office at 415-324-2490.
| Foresight Update 9 - Table of
Contents |
NASA
and Self-Replicating Systems: Implications for
NanotechnologyIn the summer of 1980, NASA and the American Society for
Engineering Education (ASEE) sponsored a summer study by 15 NASA
program engineers and 18 educators from U.S. universities to
investigate advanced automation for space missions. The resulting
400-page report included a 150-page chapter on "Replicating
Systems Concepts: Self-Replicating Lunar Factory and
Demonstration" which proposed a 20-year program to develop a
self-replicating general purpose lunar manufacturing facility (a
Self Replicating System, or SRS) that would be placed on the
lunar surface. The design was based entirely on conventional
technology.
The "seed" for the facility, to be landed on the lunar
surface from Earth to start the process, was 100 tons
(approximately four Apollo missions). Once this 100-ton seed was
in place, all further raw materials would be mined from the lunar
surface and processed into the parts required to extend the SRS.
A significant advantage of this approach for space exploration
would be to reduce or eliminate the need to transport mass from
the Earth--which is relatively expensive.
The report remarks that "The difficulty of surmounting the
Earth's gravitational potential makes it more efficient to
consider sending information in preference to matter into space
whenever possible. Once a small number of self-replicating
facilities has been established in space, each able to feed upon
nonterrestrial materials, further exports of mass from Earth will
dwindle and eventually cease. The replicative feature is unique
in its ability to grow, in situ, a vastly larger
production facility than could reasonably be transported from
Earth. Thus the time required to organize extraordinarily large
amounts of mass in space and to set up and perform various
ambitious future missions can be greatly shortened by using a
self-replicating factory that expands to the desired
manufacturing capacity."
"The useful applications of replicating factories with
facilities for manufacturing products other than their own
components are virtually limitless."
Establishing the credibility of the concept occupied the early
part of the chapter. The theoretical work of Von Neumann was
reviewed in some detail. Von Neumann designed a self-replicating
device that existed in a two-dimensional "cellular
automata" world. The device had an "arm" capable
of creating arbitrary structures, and a computer capable of
executing arbitrary programs. The computer, under program
control, would issue detailed instructions to the arm. The
resulting universal constructor was self-replicating almost as a
by-product of its ability to create any structure in the
two-dimensional world in which it lived. If it could build any
structure it could easily build a copy of itself, and hence was
self-replicating.
| Self-replicators need not be vastly complex |
One interesting aspect of Von Neumann's work is the relative
simplicity of the resulting device: a few hundred kilobits to a
megabit. Self-replicating systems need not inherently be vastly
complex. Simple existing biological systems, such as bacteria,
have a complexity of about 10 million bits. Of course, a
significant part of this complexity is devoted to mechanisms for
synthesizing all the chemicals needed to build bacteria from any
one of several simple sugars and a few inorganic salts, and other
mechanisms for detecting and moving to nutrients. Bacteria are
more complex than strictly necessary simply to self-reproduce.
Despite the relative simplicity that could theoretically be
achieved by the simplest self-reproducing systems, the proposed
lunar facility would be highly complex: perhaps 100 billion to a
trillion bits to describe. This would make it almost 10 thousand
to 100 thousand times more complex than a bacterium, and a
million times more complex than Von Neumann's theoretical
proposal. This level of complexity puts the project near the
limits of current capabilities. (Recall that a major software
project might involve a few tens of millions of lines of code,
each line having a few tens of characters and each character
being several bits. The total raw complexity is about 10 billion
bits--perhaps 10 to 100 times less complex than the proposed
SRS.) Where did this "excess" complexity come from?
The proposed SRS has to exist in a complex lunar environment
without any human support. The complexity estimate for the
orbital site map alone is 100 billion bits, and the facilities
for mining and refining the lunar soil have to deal with the
entire range of circumstances that arise in such operations. This
includes moving around the lunar surface (the proposal included
the manufacture and placement of flat cast basalt slabs laid down
by a team of five paving robots); mining operations such as strip
mining, hauling, landfilling, grading, cellar-digging and towing;
chemical processing operations including electrophoretic
separation and hydrofluoric acid leach separation, the recovery
of volatiles, refractories, metals, and nonmetallic elements and
the disposal of residue and wastes; the production of wire stock,
cast basalt, iron or steel parts; casting, mold-making, mixing
and alloying in furnaces and laser machining and finishing;
inspection and storage of finished parts, parts retrieval and
assembly and subassembly testing; and computer control of the
entire SRS.
When we contrast this with a bacterium, much of the additional
complexity is relatively easy to explain. Bacteria use a
relatively small number of well-defined chemical components which
are brought to them by diffusion. This eliminates the mining,
hauling, leaching, casting, molding, finishing, and so forth. The
molecular "parts" are readily available and identical,
which greatly simplifies parts inspection and handling. The
actual assembly of the parts uses a single relatively simple
programmable device, the ribosome, which performs only a simple
rigid sequence of assembly operations (no AI in a ribosome!).
Parts assembly is done primarily with "self-assembly"
methods which involve no further parts-handling.
Another basic issue is closure. "Imagine that the entire
factory and all of its machines are broken down into their
component parts. If the original factory cannot fabricate every
one of these items, then parts closure does not exist and the
system is not fully self-replicating." In the case of the
SRS, the list of all the component parts would be quite large. In
the case of a bacterium, there are only 2,000 to 4,000 different
"parts" (proteins). This means that the descriptions of
the parts are less complex. Because most of the parts fall into
the same class (proteins), the manufacturing process is
simplified (the ribosome is adequate to manufacture all
proteins).
What does all this mean for humanity? The report says "From
the human standpoint, perhaps the most exciting consequence of
self-replicating systems is that they provide a means for
organizing potentially infinite quantities of matter. This mass
could be so organized as to produce an ever-widening habitat for
man throughout the Solar System. Self-replicating homes,
O'Neill-style space colonies, or great domed cities on the
surfaces of other worlds would allow a niche diversification of
such grand proportions as never before experienced by the human
species."
The report concludes that "The theoretical concept of
machine duplication is well developed. There are several
alternative strategies by which machine self-replication can be
carried out in a practical engineering setting....There is also
available a body of theoretical automation concepts in the realm
of machine construction by machine, in machine inspection of
machines, and machine repair of machines, which can be drawn upon
to engineer practical machine systems capable of replication. . .
. An engineering demonstration project can be initiated
immediately, to begin with simple replication of robot assembler
by robot assembler from supplied parts, and proceeding in phased
steps to full reproduction of a complete machine processing or
factory system by another machine processing system, supplied,
ultimately, only with raw materials."
The broad implications of self-replicating systems, regardless
of scale, are often similar. The economic impact of such systems
is clear and dramatic. Things become cheap, and projects of
sweeping scale can be considered and carried out in a reasonable
time frame without undue expense.
The concepts involved in analyzing self-replicating
systems--including closure, parts counts, parts manufacturing,
parts assembly, system complexity, and the like--are also quite
similar. The general approach of using a computer (whether nano
or macro) to control a general purpose assembly capability is
also clearly supported. Whether the general-purpose manufacturing
capability is a miniature cross-section of current manufacturing
techniques (as proposed for the SRS), or simply a single
assembler arm which controls individual molecules during the
assembly process, the basic concepts involved are the same.
Finally, by considering the design of an artificial SRS in such
detail, the NASA team showed clearly that such things are
feasible. Their analysis also provides good support for the idea
that a nanotechnological "assembler" can be
substantially less complex than a trillion bits in design
complexity. There are several methods of simplifying the design
of the "Mark I Assembler," as compared with the NASA
SRS. First, it could exist in a highly controlled environment,
rather than the uncontrolled lunar surface. Second, it could
expect to find many of its molecular parts, including exotic
parts that it might be unable to manufacture, pre-fabricated and
provided in a convenient and simple format (e.g., floating
in solution). Third, it could use simple "blind,"
fixed-sequence assembly operations.
Conceptually, the only major improvements provided by the Mark I
Assembler over a simple bacterium would be the general purpose
positional control it will exert over the reactive compounds that
it uses to manufacture "parts," and the wider range of
chemical reactions it will use to assemble those
"parts" into bigger "parts." Bacteria are
able to synthesize any protein. The Mark I Assembler would be
able to synthesize a much wider range of structures. Because it
would have to manufacture its own control computer as a
prerequisite to its own self-replication, it would revolutionize
the computer industry almost automatically. By providing precise
atomic control even the Mark I Assembler will revolutionize the
manufacturing process.
Copies of "Advanced Automation for Space Missions" are
available from NTIS. Mail order: NTIS, U.S. Department of
Commerce, National Technical Information Service, Springfield,
VA. 22161. Telephone orders with payment via major credit cards
are accepted; call 703-487-4650 and request "N83-15348.
Advanced Automation for Space Missions." Purchase price is
about $40.00, various shipping options are available.
Dr. Merkle's
interests range from neurophysiology to computer security; he is
a researcher at Xerox Palo Alto Research Center.
| Foresight Update 9 - Table of
Contents | Page1 | Page2 | Page3 | Page4 | Page5 |
From Foresight Update 9, originally
published 30 June 1990.
Foresight thanks Dave Kilbridge for converting Update 9 to
html for this web page.
| Foresight Update 9 - Table of Contents | ||
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