The death of artificial life

I recently read Steven Levy’s book on Artificial Life. I enjoyed the book very much, since the a-life theme weaves together many of the threads of research into complex adaptive systems, and is a useful way of thinking about the relationship between the various topics. Levy also tells a human story of the scientific pursuit of artificial life, the tale of a motley crew of eccentric scientists, pursuing their work at the margins of the scientific mainstream, who join together to create a rich new area for exploration.

The book was written in 1992; ten years later, the results of the pursuit of a-life have been decidedly mixed. Despite substantial scientific progress, the more ambitious ideas of artificial life seem to have retreated to the domain of philosophy. And as a scientific field, the study of artificial life seems to have returned to the margins. The topic is fascinating, and the progress seems real — why the retreat? One way to look at progress and stasis in the field is to consider how scientists filled in the gaps of von Neumann’s original thesis. The brilliant pioneer of computer science, in Levy’s words, “realized that biology offered the most powerful information processing sytem available by far and that its emulation would be the key to powerful artificial systems.” Considering reproduction the diagnostic aspect of life, von Neumann proposed a thought experiment describing a self-reproducing

The automaton was a mechanical creature which floated in a pond that happened to be chock full of parts like the parts from which the creature was composed. The creature had a sensing apparatus to detect the parts, and a robot arm to select, cut, and combine parts. The creature read binary instructions from a mechanical tape, duplicated the instructions, and fed the instructions to the robot arm, which assembled new copies of the creature from the parts floating in the pond. The imaginary system implemented two key aspects of biological life:
* a genotype encoding the design for the creature, with the ability to replicate its own instructions (like DNA)
* a phenotype implementing the design, with the ability to replicate new creatures (like biological reproduction)

The thought experiment is even cleverer than it seems — von Neumann described the model in the 1940s, several years before the discovery of DNA!

In the years since von Neumann’s thought experiment, scientists have conceived numerous simulations that implement aspects of living systems that were not included in the original model:

* Incremental growth. The von Neumann creature assembled copies of itself, using macroscopic cutting and fusing actions, guided by a complex mechanical plan. Later scientists developed construction models that work more like the way nature builds things; by growth rather than assembly. Algorithms called L-systems, after their inventor, biologist Astrid Lindenmeyer, create elaborate patterns by the repeated application of very simple rules. With modification of their parameters, these L-systems generate patterns that look remarkably like numerous
species of plants and seashells. (There is a series of wonderful-looking books describing applications of the algorithms).
* Evolution. Von Neumann’s creature knows how to find parts and put together more creatures, but it has no ability to produce creatures that are different from itself. If the pond gradually dried up, the system come to a halt; it would not evolve new creatures that could walk instead of paddle. John Holland, the pioneering scientist based at the University of Michigan, invented a family of algorithms that simulate evolution. Instead of copying the plan for a new creature one for one, the genetic algorithm simulates the effect of sexual reproduction by
occasionally mutating a creature’s instruction set and regularly swapping parts of the instruction sets of two creatures. One useful insight from the execution of genetic algorithm simulations is that recombination proves to be a more powerful technique for generating useful adaptation than mutation.
* Predators and natural selection. In von Neumann’s world, creatures will keep assembling other creatures until the pond runs out of parts. Genetic algorithms introduce selection pressure; creatures that meet some sort of externally imposed criterion get to live longer and have more occasions to reproduce. Computer scientist Danny Hillis used genetic algorithms to evolve computer programs that solved searching
problems. When Hillis introduced predators in the form of test programs that weeded out weak algorithms, the selection process generated stronger results.

Genetic algorithms have proven to be highly useful for solving technical problems. They are used to solve optimization problems and model evolutionary behavior in fields of economics, finance, operations,
ecology, and other areas. Genetic algorithms have been used to synthesize computer programs that solve some computing problems as well as humans can.

* Increasingly complex structure. Evolution in nature has generated increasingly complex organisms. Genetic algorithms simulate part of the process of increasing complexity. Because the recombination process
generates new instruction sets by swapping of large chunks of old instruction sets, the force of selection necessarily operates on modules of instructions, rather than individual instructions (see Holland’s book, Hidden Order, for a good explanation of how this works).
* Self-guided motion. Von Neumann’s creatures were able to paddle about and find components; how this happens is left up the the imagination of the reader — it’s a thought experiment, after all. Rodney Brooks’ robot
group at the MIT AI lab has created simple robots, modeled after the behavior of insects, which avoid obstacles and find things. Instead of using the top-heavy techniques of early AI, in which the robot needed to
build a conceptual model of the appearance of the world before it could move, the Brooks group robots obey simple rules like moving forward, and turning if it meets an obstacle.
* Complex behavior. Living systems are complex, a mathematical term of art for systems that are composed of simple parts whose behavior as a group defies simple explanation (concise definition lifted from Gary
). Von Neumann pioneered the development of cellular automata, a class of computing systems that can generate complex behavior. John Conway’s Game of Life implemented a cellular automaton that proved to be
able to generate self-replicating behavior (apparently after the Levy book was published), and, in fact, was able to act as a general-purpose computer (Flake’s chapter on this topic is excellent). Cellular automata can be used to simulate many of the complex, lifelike behaviors described below.
* Group behavior. Each von Neumann creature assembles new creatures on its own, oblivious to its peers. Later scientists have devised methods of ways of simulating group behavior: Craig Reynolds simulated bird flocking behavior, each artificial bird following simple rules to avoid collisions and maintain a clear line of sight. Similarly, a group of scientists at the Free University in Brussels simulated the collective foraging behavior of social insects like ants and bees. If a creature finds food, it releases pheremone on the trail; other creatures
wandering randomly will tend to follow pheremone trails and find the food. These behaviors are not mandated by a leader or control program, they emerge naturally, as a result of each creature obeying a simple set.
of rules.

Like genetic algorithms, simulations of social insects have proven very useful at solving optimization problems, in domains such as routing and scheduling. For example scientists Erik Bonabeau and Marco Dorigo used
ant algorithms to solve the classic travelling salesman program.

* Competition and co-operation. Robert Axelrod simulated “game theory” contests, in which players employed different strategies for co-operation and competition with other players. Axelrod set populations
of players using different algorithms to play against each other for long periods of time; players with winning algorithms survived and multiplied, while losing species died out. In these simulations, co-operative algorithms tend to predominate in most circumstances.

* Ecosystems. The von Neumann world starts with a single pond creature, which creates a world full of copies of itself. Simulators Chris Langton, Steen Rasmussen and Tom Ray evolved worlds containing whole ecosystems worth of simulated creatures. The richest environment is Tom Ray’s Tierra. A descendant of “core wars,” a hobbyist game written in assembly language, the Tierra universe evolved parasites, viruses, simbionts, mimics, evolutionary arms races — an artificial ecosystem full of interations that mimic the dynamics of natural systems. (Tierra is actually written in C, but emulates the computer core environment. In the metaphor of the simulation, CPU time serves as the “energy” resource and memory is the “material” resource for the ecosystem. Avida, a newer variant on Tierra, is maintained by a group at CalTech).
* Extinction. Von Neumann’s creatures will presumably replicate until they run out of components, and then all die off together. The multi-species Tierra world and other evolutionary simulations provide a more complex and realistic model of population extinction. Individual species are frequently driven extinct by environmental pressures. Over a long period of time, there are a few large cascades of extinctions, and many extinctions of individual species or clusters of species. Extinctions can be simulated using the same algorithms that describe
avalanches; any given pebble rolling down a steep hill might cause a large or small avalanche; over a long period of time, there will be many small avalances and a few catastrophic ones.
* Co-evolution. Ecosystems are composed of multiple organisms that evolve in concert with each other and with changes in the environment. Stuart Kauffman at the Santa Fe institute created models that simulate the evolutionary interactions between multiple creatures and their environment. Running the simulation replicates several attributes of evolution as it is found in the historical record. Early in an evolutionary scenario, when species have just started to adapt to the environment, there is explosion of diversity. A small change in an organism can lead to a great increase in fitness. Later on, when species become more better adapted to the environment, evolution is more likely to proceed in small, incremental steps. (see pages 192ff in Kauffman’s At Home in the Universe for an explanation.)
* Cell differentiation. One of the great mysteries of evolution is the emergence of multi-celled organisms, which grow from a single cell. Levy’s book writes about several scientists who have proposed models of cell differentiation. However, these seem less compelling than the other models in the book. Stuart Kauffman developed models that simulate a key property of cell differentiation — the generation of only a few basic
cell types, out of a genetic code with the potential to express a huge variety of patterns. Kaufman’s model consists of a network in which each node is influenced by other nodes. If each gene affects only a few other genes, the number of “states” encoded by gene expression will be proportional to the square root of the number of genes.
There are several reasons that this model is somewhat unsatisfying. First, unlike other models discussed in the book, this simulates a numerical result rather than a behavior. Many other simulations could create the same numerical result! Second, the empirical relationship between number of genes and number of cell types seems rather loose — there is even a dispute about the number of genes in the human genome!

Third, there is no evidence of a mechanism connecting epistatic coupling and the number of cell types. John Holland proposed an “Echo” agent system to model differentiation (not discussed in the Levy book). This model is less elegant than other emergent systems models, which generate complexity from simple rules; it starts pre-configured with multiple, high-level assumptions. Also, Tom Ray claims to have made progress at modeling differentiation with the Tierra simulation. This is not covered in Levy’s book, but is on my reading list.

There are several topics, not covered in Levy’s book, where progress seems to have been made in the last decade. I found resources for these on the internet, but have not yet read them.
* Metabolism. The Von Neumann creature assembles replicas of itself out of parts. Real living creatures extract and synthesize chemical elements from complex raw materials. There has apparently been substantial progress in modelling metabolism in the last decade; using detailed models gleaned from biochemical research.
* Immune system. Holland’s string-matching models seems well-suited to simulating the behavior of the immune system. In the last decade, work has been published on this topic, which I have not yet read.
* Healing and self-repair. Work in this area is being conducted by IBM and the military, among other parties interested in robust systems. I have not seen evidence of effective work in this area, though I have not searched extensively.
* Life cycle. The von Neumann model would come to a halt with the pond strip-mined of the raw materials for life, littered with the corpses of dead creatures. By contrast, when organisms in nature die, their bodies
feed a whole food chain of scavengers and micro-organisms; the materials of a dead organism serve as nutrients for new generations of living things. There have been recent efforts to model ecological food chains
using network models; I haven’t found a strong example of this yet. Von Neumann’s original thought experiment proposed an automaton which would replicate itself using a factory-like assembly process, independent of its peers and its environment. In subsequent decades, researchers have made tremendous progress at creating beautiful and useful models of many more elements of living systems, including growth, self-replication, evolution, social behavior, and ecosystem interactions.

These simulations express several key insights about the nature of living systems.
* bottom up, not top down. Complex structures grow out of simple components following simple steps.
* systems, not individuals. Living systems are composed of networks of interacting organisms, rather than individual organisms in an inert background.
* layered architecture. Living and lifelike systems express different behavior at different scales of time and space. On different scales, living systems change based on algorithms for growth, for learning, and for evolution.
Many “artificial life” experiments have helped to provide a greater understanding of the components of living systems, and these simulations have found useful applications in a wide range of fields. However, there has been little progress at evolving more sophisticated, life-like systems that contain many of these aspects at the same time.

A key theme of the Levy book is the question of whether “artificial life” simulations can actually be alive. At the end of the book, Levy opend the scope to speculations about the “strong claim” of artificial
life. Proponents of a-life, like proponents of artificial intelligence, argue that “the real thing” is just around the corner — if it is not a property of Tierra and the MIT insect robots already!

For example, John Conway, the mathematics professor who developed the Game of Life, believed that if the Game was left to run with enough space and time, real life would eventually evolve. “Genuinely living,
whatever reasonable definition you care to give to it. Evolving, reproducing, squabbling over territory. Getting cleverer and cleverer. Writing learned PhD theses. On a large enough board, here is no doubt in
my mind that this sort of thing would happen.”(Levy, p. 58) That doesn’t seem imminent, notwithstanding Ray Kurzweil’s opinions that we are about to be supplanted by our mechanical betters.

Nevertheless, it is interesting to consider the point at which simulations might become life. There are a variety of cases that test the borders between life and non-life. Does life require chemistry based
on carbon and water? That’s the easiest of the border cases — it seems unlikely. Does a living thing need a body? Is a prion a living thing? A self-replicating computer program? Do we consider a brain-dead human whose lungs are operated by a respirator to be alive? When is a fetus considered to be alive? At the border, however, these definitions fall into the domain of philosophy and ethics, not science.

Since the creation of artificial life, in all of its multidimensional richness, has generated little scientific progress, practitioners over the last decade have tended to focus on specific application domains, which continue to advance, or have shifted their focus to other fields.

* Cellular automata have become useful tools in the modeling of epidemics, ecosystems, cities, forest fires, and other systems composed of things that spread and transform.
* Genetic algorithms have found a wide variety of practical applications, creating a market for software and services based on these simulation techniques.
* The simulation of plant and animal forms has morphed into the computer graphics field, providing techniques to simulate the appearance of complex living and nonliving things.
* The software for the Sojourner robot that expored Mars in 1997 included concepts developed by Rodney Brooks’ team at MIT; there are numerous scientific and industrial applications for the insect-like robots.
* John Conway put down the Game and returned to his work as a mathematician, focusing on crystal lattice structure.
* Tom Ray left to the silicon test tubes of Tierra, and went to the University of Oklahoma to study newly-assembled genome databases for insight into gene evolution and human cognition. The latest
developments in computational biology have generated vast data sets that seem more interesting than an artificial world of assembly language parasites.

While the applications of biology to computing and computing to biology are booming these days, the synthesis of life does not seem to be the most fruitful line of scientific investigation. Will scientists ever evolve life, in a computer or a test tube? Maybe. It seems possible to me. But even if artificial creatures never write
their PhD thesis, at the very least, artificial life will serve the purpose of medieval alchemy. In the pursuit of the philosophers stone early experimenters learned the properties of chemicals and techniques for chemistry, even though they never did found the elixir of eternal life.

What Went Wrong with What Went Wrong

Based on a recommendation from a blog reader, I picked up “What Went
Wrong: Western Impact and Middle Eastern Response
” by Bernard Lewis.
Given the mixed Amazon reviews, I borrowed the book from the library.
The obvious criticisms of the book’s style are correct — What Went
Wrong is a collection of transcribed lectures, hastily taken to print
after September 11th. The essays are not edited together to support a
thesis, and they do not provide a satisfying answer the question in the
book’s title.
Even so, one might expect that lectures given by one of the world’s
leading experts in Middle Eastern history might contain substantive
information based on primary source research, combined with insightful
interpretations and a powerful, implicit argument driven by the
scholar’s point of view, developed through decades of thought on the
topic. Such a book would be worth reading, though it would require more
work by the reader to assemble the thesis by means of marginal notes.
The book has interesting facts and stories. But Lewis’ interpretations
are badly inadequate, even from the perspective of someone with a
sketchy understanding of Muslim history.
The subject of the book is the response of the “Middle East” to
increasingly evident Western economic and military superiority in modern
times. Lewis is an expert on the Ottoman empire, and the book focuses
primarily on the Ottoman Turks, secondarily on Iran, and very little on
Arab regions (not at all on other Muslim countries which are out of the
book’s scope).
After several painful defeats in the late 17th century to European
armies, Ottoman rulers initiated a series of campaigns to study and
integrate Western military, economic, and technological advances.
The trouble is that Lewis seems to take for granted the flaws in Ottoman
culture that he purports to explain. Lewis reports that initiative to
learn from Europeans was a traumatic change. “For Muslims, first in
Turkey and later elsewhere, this brought a shocking new idea that one
might learn from the previously despised infidel.” The Ottoman rulers
turned to the Ulema, the masters of Islamic law, and requested an
exemption from the traditional prohibition against accepting infidel
Yet the intellectual insularity shown by the Ottoman empire was not
typical of earlier Islamic regimes, which embraced and integrated
external cultural influences and non-Muslim expertise. Baghdad, the
capital city of the Abbasid dynasty, was laid out by a Jewish
mathematician and a Persian astronomer. Al-Khwarizmi, the Muslim
mathematician, explained the Indian number system in Arabic, and made
innovative contributions to algebra. Abd al-Rachman III, the ruler of
Muslim Spain at the height of its power and cultural influence, had a
Jewish vizier, Hasdai ibn Shaprut.
Lewis explains the Ottoman ignorance of Western ways as an outcome of
Muslim prohibitions against traveling and settling in foreign lands.
This geographical insularity also was not typical of earlier Muslim
regimes. In the medieval era, the Muslim world was a key link in a world
system of trade that linked Europe and Asia. Muslim merchants spent
their lives in caravans and ships; there were longstanding Muslim
settlements in Southeast Asia and China.
The interesting question is not why the belated efforts of the Ottoman
empire to adopt infidel knowledge failed. With its underlying attitudes
toward “foreign influence” it does not seem so surprising that these
efforts were too little, too late. The question is why the Ottoman
empire was so much more insular and narrow-minded than the Muslim
regimes that came before it.
Lewis does mention the decline in Muslim science since medieval times.
In the medieval era, Muslim scientists sought out Greek, Indian, and
Persian knowledge, and made innovative contributions to mathematics,
astronomy, and medicine. By the Ottoman period, Muslim scientists were
no longer seeking new sources and adding to the world’s store of
knowledge, “they had their own science, handed down by great scientists
of the past.” What happened to the Muslim intellectual tradition in the
mean time that destroyed its ability to learn and innovate?
Lewis writes that Ottoman efforts to jumpstart the economy by importing
factories failed to take root. But he includes no evidence or analysis
of underlying economic structures that might have inhibited or fostered
economic progress. Two points of comparison. Throughout the medieval
era, the Muslim world played a major role in international trade. In the
16th century and later, European ships discovered alternate sea routes
to the Far East, and established permanent colonies, cutting out the
Muslim segment of the trade route. In 1568, the Ottomans drew up a plan
to dig a canal through Suez, to render the Red Sea route competitive
again. The following year, they started to dig a canal between the Don
and the Volga rivers, to improve the northern trade route. But these
plans were abandoned, in favor of head-on war with Russia and Vienna.
Why did the Ottoman military initiatives supersede economic ones; did
they miss the connection between money and power, or did they believe
that territorial conquest would serve them better?
In contemporary era, the Arab regions were graced with oil wealth. They
imported unskilled Chinese laborers to build oil platforms and
refineries. The Chinese workers learned the technology, saved their
money, and within a generation had developed world-leading businesses in
construction and transportation logistics. Why didn’t Arabs take
advantage of their privilege and money to move up the value chain and
dominate the worldwide oil, chemical, and shipping industries?
One might attribute Middle Eastern economic stagnation to flaws in the
Muslim legal and financial systems. Lewis doesn’t make this argument,
but he does make much of the fact that concept idea of secular law comes
from the Christian world, where a separation between church and state
was needed to keep chronic religious wars from wrecking society. Lewis
explains that European colonial and post-colonial regimes imposed
systems of secular, Western law, which were sometimes adopted and often
resisted by Middle Easterners. Anti-Western Muslim governments throw
off the imported systems, and return to the Sharia, the traditional
Muslim law code.
Contemporary Sharia systems in places like Iran and Afghanistan are
often mocked for being medieval and backward, legislating repression of
women and brutal corporal punshment (no, I’m not in favor of the Texas
death penalty, either). But there is no empirical reason that a system
of Muslim jurisprudence needs to be backward. After all, European laws
once featured trial by ordeal, and prevented women from owning property.
A living tradition of Muslim law might be able to adapt to current
economic and social conditions. How did the Sharia change from a system
that had once reflected the standards of justice of its time to one that
insisted on avoiding change?
Lewis writes that Western ideas of equal rights and democracy, which
underlie Western legal systems, likewise caught on slowly in the Middle
East, and were often imposed by outsiders. Colonial and
Western-dominated post-colonial regimes insisted on full rights for
non-Muslims, and the ending of slavery (though they ignored restrictions
on women). Ideas of liberty were sometimes used by internal reformers,
but were often resisted as foreign grafts.
But there is no logical reason that Islam itself could not make these
changes — even without a secular system. Islam is based on ideals of
equality and justice — why could these ideas not be extended to
enfranchise women, free slaves, and institutionalize the rights of
non-Muslims, as they were practiced in the most tolerant Islamic
societies. Likewise, there is a Muslim tradition of consultative
government. Why has this not been developed into a system of government
that takes into account the voices and needs of different sectors of
Lewis’ analysis of the failure of the Middle East to adopt Western
technology is weak and superficial. Lewis provides some interesting
primary-source documentation about the slow adoption of modern clocks
and calendars into Ottoman administration. The resistance to modern
timekeeping is illustrated with anecdotes of the leisurely pace of life,
even today, in Middle Eastern countries. But Lewis doesn’t ask the
interesting questions about why the technology of time was ignored. In
Western society, technologies of time were adopted in government and
business administration, industrial production, and transportation. The
Ottoman empire had a fairly advanced administrative system. What was
missing in Ottoman government and economic institutions that they did
not see the benefit of these technologies, or were unable to implement them?
Norvell De Atkine, the US military trainer, argues that contemporary
Middle Eastern armies failed to successfully assimilate modern weapons,
not because of lack of technology, but because of flaws in
organizational culture. Middle Eastern governments brought in Western
trainers and technology, but the troops were unable to use and maintain
the systems because of their aversion to sharing information. An officer
trained in the use of a weapons system would not share that knowledge
with rest of his men, because sharing knowledge would reduce his power.
Did Ottoman armies and administrations have these problems sharing
information — is this what made it diffiicult to embrace new technology
and methods? In the early days of Muslim conquest, were armies this bad
at communicating, and successful nevertheless? Lewis doesn’t say.
Some of Lewis’ explanations about the Middle East’s failure to
Westernize are simply laughable. Lewis makes much out of the reluctance
of Middle Easterners to appreciate European classical music. Lewis
attributes Middle Eastern indifference to European classical music to a
general aversion to foreign influence, and in particular to a dislike of
polyphonic technique, which uses the same organizational genius as
Western team sports, parliamentary government, and corporate structures.
Lewis doesn’t notice the many and substantial foreign influences on
Middle Eastern music, which come from the East instead of the West.
Muslim classical musical styles were heavily influenced by Indian and
pre-Muslim Persian styles. Popular Middle Eastern music is full of
influences from Central and Eastern Europe. Today, music from India is
extremely popular in the Middle East. Muslims do like foreign music,
they just happen to find eastern styles more congenial than western styles!
By contrast, Lewis talks approvingly of the adoption of European
architectural styles. He does not mention that medieval Muslim empires
created their distinctive architectural styles from the elements of
existing buildings. In Eastern regions of Muslim dominance, mosques were
converted from Byzantine churches. In medieval Spain, Muslim took the
columns, literally and figuratively, from the ruins of Roman buildings.
Muslim architecture always incorporated foreign influences; this was the
rule, not the exception.
Throughout the book Lewis describes the tensions between modernizers,
who wished to replace the traditions of Muslim society with European
imports, and traditionalists, who wished to recover a lost world of
cultural purity. Lewis himself seems to agree with the assumptions
underlying this debate, and he takes the side of the modernizers. Lewis
seems to embrace the assumption that a strong civilization builds its
own culture out of native materials; but a weak civilization needs to
adapt to cultural norms of the stronger power. Lewis doesn’t consider
that a strong civilization is one which is able to embrace, absorb and
transform diverse influences. In other words, Lewis makes the same
mistake as the subjects of his historical inquiry.
Here’s what I take away from the book, based on Lewis’ evidence and
other reading. The decline in Muslim civilization occured long before it
the evident decline of the Ottoman empire. The Ottoman empire was
militarily powerful in its day, and wealthy at its prime, but it lacked
the cultural flexibility required to innovate and adjust to change.
But why was the Ottoman empire so insular and inflexible? Lewis
describes the phenomenon, but doesn’t explain it.
By the way, I haven’t read Said’s Orientalism (yet), which criticizes
Bernard Lewis in particular, and Western scholarship in general, for
colonalist and racist stereotypes of the inferiority of Muslim cultures.
The problem with What Went Wrong isn’t that Lewis’ criticisms are
biased, it is that they are shallow; they don’t explain very real flaws
of Middle Eastern societies in modern times, which are flaws even with
respect to the greatest historical achievements of Muslim civilization.

The Ornament of the World: How Muslims, Jews, and Christians Created a Culture of Tolerance in Medieval Spain

The Ornament of the World, by Maria Menocal, is a fascinating but
flawed book about Muslim culture in medieval Spain. The exciting parts of
the book are the stories of cultural influence among Muslims, Jews, and
Christians. These cultural influences shed light on some fundamental
chapters in history that are told often but explained poorly.
* You may have learned in European history class that medieval Arab
culture preserved Greco-Roman classical knowledge during the Europe’s
dark ages. Menocal’s book tells the story how classical works of science
and philosophy, preserved in Arabic, were transmitted to Christian
Europe. In the 8th-10th centuries, most of the Iberian peninsula was
ruled by the Umayyad dynasty, with Cordoba as its capital. The Umayyad
rulers, in competition with the Abbassid Caliphate based in Baghdad,
established Cordoba as a center of higher learning, building an
extensive library and funding leading scholars.
In the 11th century, the Umayyad government fell, the Iberian peninsula
became divided into dozens of warring city-states, and Christian rulers
from the North of Spain gradually increased their domains. The
Christian-controlled areas continued to be heavily influence by Muslim
culture. Alfonso IV of Castile, ruler of the Taifa of Toledo, wanted to
publicize this learning within Christian Europe, and funded the
translation process. Jewish and Arab scholars read texts in Arabic, and
recited them out loud in Castilian. Christian scholars listened to the
spoken Castilian and wrote in Latin.
* If you studied European literature, you probably have some
recollection of the troubadours of Provence, who pioneered the poetry of
courtly romance. In the 11th to13 centuries, a seemingly remote region
in the south of today’s France, heretofore known for bloody turf wars
between rival Frankish feudal lords, suddenly produced a flowering
musical and literary culture. Where did this surge of civilization come
The region of Provence is located on the Northeast side of the
Pyrenees. The constant warfare among the citystates of the Iberian
peninsula offered attractive opportunities for free-lance Frankish
knights, who crossed the mountains to seek their fortune, and helped to
conquer Muslim cities. These knights were captivated by the music and
poetry of Andalusian culture, and returned to Provence, bringing with
them groups of professional singers of Arabic songs, traditions of
stylized lyric poetry, and romantic conceptions of love.
* If you have a basic background in Jewish history and philosophy, you
may recall the Kuzari, medieval work by Judah Halevi. The frame-story
of the Kuzari is the correspondence between a Jewish scholar and the
King of a central Asian tribe called the Khazars, who requested an
explanation of various beliefs and philosophies; in order to introduce
the best tradition to his people. The Kuzari includes logical “proofs”
of the existence of God, and arguments for the superiority of revealed
religions truth to philosophies based on reason.
Menocal tells more of the story. The correspondence with the Khazars
was conducted several generations earlier, in the 10th century, by
Hasdai ibn Shaprut, the foreign minister to the Umayyad caliph Abd
al-Rachman III. That correspondence compared Judaism with Christianity
and Islam. Halevi lived and worked two hundred years later, and was a
student of Moses Ibn Eza, philologist, poet, and fan of the Andalusian
culture, in a time when all three monotheistic faiths struggled with the
implications of Greek philosophy. Halevi spent most of his career as a
peripatic scholar and poet in Jewish intellectual circle. Later in his
life, he had a change of heart, and advocated a return to Judaism cleansed of the corruptions of
secular life and philosophical influences. He wrote the Kuzari arguing
that philosophy is incompatible with faith, wrote beautiful poems about Israel in exile, yearning for God, and he died on a pilgrimage to crusader-controled Jerusalem.
Menocal writes in a romantic and nostalgic style that derives in part
from her subjects own elegaic esthetic, and from her own nostalgia for
the world of Andalusia. Sometimes the style works, especially when
describing works of architecture built as monuments and memorials. She
describes the initial design of the Alhambra palace gardens: “The first
gardens built on the red hill by those exiles from Cordoba were, like
Abd al-Rahman’s palm tree, the echoes and reconstructed memories of a
mourned homeland.”
Sometimes the romantic language is overwrought and awkward, as in these
description of the writing of Shmuel Hanagid, the vizier of Grenada,
military general, Jewish communal leader and Hebrew poet. “The third
poem, to praise the third victory, had flowed most easily of all, and he
could now more effortly flex those new muscles that sang of arms and men
and God… In that loving and revolutionary embrace by a powerful and
supremely self-assured man, Heberew was redefined, and cultivated as a
language that could transcend the devotional and theological uses to
which it had lately been limited.”
Particularly irritating is the use of purple prose to cover the lack of
information. For example, the author describes the libraries of Cordoba
as follows: “The rich web of attitudes about culture, and the
intellectual opulence that it signified, is perhaps only suggested by
the caliphal library of, by one count, some four hundred thousand
volumes, and this at a time when the largest library in Christian Europe
probably held no more than 400 manuscripts.”
An impressive collection of books, to be sure. But who read those books?
What classes of society were literate? What role did higher education
play in society? What was a typical curriculum? Were the books mostly
copies of classical manuscripts, or did they include new scholarship?
No answers, just vague sentences such as: “Just as essential to the
social and cultural project embedded in those libraries was a series of
attitudes about learning of every sort, about the duty to transmit
knowledge from one generation to another, about the interplay between
the very modes of learning that were known to exist…”
The book provides context for a better understanding of the history of
Christian, Muslim, and Jewish cultures, sheds light on a fascinating
historical period, and whets ones appetite for more information. It is
definitely worth reading.

The Mapmakers

While on the road, I read The Mapmakers, by John Noble Wilford, Pulitzer prize-winning science writer for the New York Times.
The book tells the stories of the scientists and explorers who pioneered the techniques and practice of mapmaking. The book explains early ingenious efforts to measure the size and shape of the earth, and the invention of techniques for surveying territory and projecting the sphere of the earth onto paper. Wilford is particularly good at telling tales of pre-20th century adventurers:
* the Frenchmen who travelled to Lapland and Peru to figure out how the sphere of the earth is out of true
* John Harrison, the watchmaker with working class origins, who built the first clock precise and reliable enough to measure longitude, and fought the aristocratic science establishment that refused to give him credit for the discovery
* James Cook and George Vancouver, who added the coasts of the South Pacific and Western North America on European maps, and subtracted the Northwest Passage and the lush, legendary Terra Australis.
* The members of the India Survey who infiltrated and mapped Chinese-controlled Tibet in the 1860s while posing as lamas, including Nain Singh, who used a prayer wheel to store slips of paper with compass and distance measurements instead of prayers, paced off distances with rosaries containing 100 beads instead of the traditional 108, and carried a sextant, compass, thermometer and mercury container in a false-bottomed box.
The book slows down somewhat with the advent of 20th century team science, but still tells interesting stories about the use of new technology to map previously inaccessible territory; side-looking radar under clouds in Amazon rain forest, radio echo sounding under the Antarctic ice sheet, seismic mapping under the earth, sonar under the ocean floor, satellites and spacecraft on the moon and Mars.
The Mapmakers purports to be world history, but it has a strong European focus. Wilford does include few pages about sophisticated early mapmaking practices in China. But he almost completely ignores Muslim and Indian geography. The book contains just one brief reference to ibn Khaldun, the medieval Muslim traveler and geographer, and nothing on Al Idrisi, who was commissioned by Roger II, the Christian king of Sicily, to update navigational records, and created the famous early atlas called “The Book of Roger.” The Mapmakers briefly mentions that one Francis Wilford, a member of India Survey, was a student of ancient Hindu geography. Given early Indian sophistication in astronomy, math, and government administration, one wonders what earlier sources of geographic knowledge he drew on. According to an Indian friend of mine, many early maps were destroyed to keep them out of the hands of British colonial rulers.
Wilford writes about the dire level of geographic ignorance of Medieval Europeans, whose maps routinely placed Paradise at the Eastern border of China, without noting that during the same period, there was a longstanding, ongoing system of travel and trade from Arabia through India and Southeast Asia to China (see books by Abu Lughod and KN Chaudhuri, among others), conducted by Arabs, Jews, Indians, and sometimes Chinese. I don’t know what sorts of maps were used by these travelling merchants, but they must have used something, because they got from place to place regularly and routinely.
Wilford tells the story of mapmaking as a process of technological development and scientific discovery. Readers are left on their own to infer the social contexts of mapmaking from the details of the tales of “exploration”: in the 16th-19th centuries, European colonial expansion; in the 20th century, the hunt for oil and gas resources, and the advances of military missiles, and submarines, and spy satellites. The sociopolitical history of mapmaking is a different book than the one Wilford wrote; that would also be and interesting story to read.

Why Do Arabs Lose Wars These Days?

A retired senior US military trainer writes a scathing critique of Arab military culture in American Diplomacy. Based on personal experience training Arab officers and soldiers, and research into Arab military history, Norvelle de Atkine observes that:
“* Arab officers are not concerned about the welfare and safety of their men.
* The Arab military mind does not encourage initiative on the part of junior officers, or any officers for that matter.
* Responsibility is avoided and deflected, not sought and assumed.
* Political paranoia and operational hermeticism, rather than openness and team effort, are the rules of advancement (and survival) in the Arab military establishments.”
If De Atkine is right, then why are Arabs so much worse at war these days?
In the initial ages of Muslim expansion and world leadership (7th-11th centuries), Arabs had formidable military might. In later centuries (13th-17th), Muslim powers built empires through military prowess, often with armies of Turkish or Central Asian origin.
What’s happened since? Have there been changes in Arab culture in general, or Arab military culture in particular that render their armies less effective? Has the culture remained the same, while war has changed in modern times? Is there any cultural connection between the old Arab military powers and today’s squabbling, hierarchy-bound, poorly-trained troops. Is there a persuasive argument that European colonialism caused the decline?
I’m fairly new to the study of Muslim history; would love plausible explanations and good references from folks who are knowledgable about the subject.
De Atkine, by the way, seems to be an equal opportunity critic — here’s his analysis of the US military’s persistent inability to train people and develop skills to fight “small wars.”

Can the US Win Small Wars? Do We Want To?

Recently read “The Savage Wars of Peace: Small Wars and the Rise of American Power“, by Max Boot, whose editorial features editor at the Wall Street Journal.
In a nutshell — the history is lively and informative; the ideology is insane.
The book makes a persuasive case against the Powell Doctrine, and a scary, unpersuasive argument in favor of imposing a Pax Americana around the world.
Boot tells the stories of many small wars fought by the US throughout its history: suppression of North African pirates; invasions and occupations in the Carribean and Central America, counterinsurgency in the Phillipines, protection of Americans in crumbling Imperial China. These wars were fought to protect American trade, to avenge attacks on American soil, defend the lives of Americans abroad, and to ensure friendly governments in areas the US wanted to control. Some small wars were quite short, others involved military occupations that lasted years or decades. These “small wars” are much less well known than the major conflicts, and, Boot argues, the historical lessons of these wars have been forgotten.
These stories show how the US developed highly effective tactics for fighting guerillas and irregular armies:
* use small, flexible forces
* use bluff, daring, and fighting skill to intimidate and kill opponents
* reduce the guerilla’s support among the local population by befriending and defending local people, improving sanitation and healthcare, building roads and bridges, and helping to establish local self-government
* use local knowledge to identify the enemy and avoid indiscriminate killing
Boot uses his historical analysis to soundly discredit the Powell Doctrine, which has shaped US military policy in recent decades. In reaction to the US failure in Vietnam, the Powell doctrine states that wars should be fought only when the US can stage an overwhelming attack and achieve rapid victory, incurring few casualties; and leave quickly, following a defined “exit strategy”, without becoming embroiled in “nation-building.”
Boot draws very different conclusions from Vietnam. The US military failed in Vietnam, not because they didn’t fight a conventional war aggressively enough, but because they used conventional tactics against a guerrilla army. The book includes a compelling step-by-step analysis of the flaws in the execution of the Vietnam war, based on the historical lessons of past wars against guerrilla forces. The book considers recent U.S. military engagements, in Iraq, Bosnia, Somalia, Haiti, and Kosovo, and explains how the Powell doctrine gets in the way of effective use of US military policy.
The book’s history is well-researched, its argument is well-constructed, the writing is vivid and clear. Its philosophy is also highly troubling. Boot is an aggressive apologist for US imperial policies. He argues rather unpersuasively that trade was a minor factor in U.S. “small wars.” He is correct that trade with the countries in question accounted for a small proportion of US business; but that is irrelevant, a small number of influential businesspeople with a grievance can have a disproportionate impact on policy, as can be seen in recent resurgence of steel tariffs and mohair subsidies. Instead, Boot makes the case that the US went to war largely for moral reasons. He argues repeatedly that US military interventions and occupations were humane on the whole, and whenever US rule was less than perfect, it was less cruel than European colonial masters, and more fair and competent than rule by brutal and greedy locals.
At times, the apologies for imperialism verge on the laughable. Boot describes US missionaries in China as “predecessors to today’s human rights workers”, with no awareness that locals might resent foreigners’ attempts to change their beliefs and culture. Boot states with no irony that “the 19th century free trade system was protected and expanded by the British Royal Navy.” No qualifications about the relative levels of “freedom” in, say, British-Indian commerce.
In fact, Boot is an unabashed imperialist. He argues that the US has a responsibility to use military might to impose a Pax Americana, establishing order and imposing government in chaotic regions all over the world. He has no qualms about playing the role of “world police”. The goal of a civic police force is not to end crime but to identify and catch criminals; likewise, the goal of “world police force” is not to win wars but to stop malefactors and keep order. Boot sees that US vacillation encourages our enemies, and believes that a more aggressive US policy would help to deter violence.
Boot likes war altogether too much. He enthusiastically recounts tales of heroism: valiant hill charges, crafty ambushes, and noble endurance against pain, weather, and odds. The book is spiced with tales of gruesome violence — beheadings, impalings, disembowlings, and numerous other forms of injury and torture. The vivid style reads like it was written by someone who grew up reading too many Western novels.
Boot was born in 1971; his family immigrated from Russia in 76. He was raised in Los Angeles, went to Berkeley for an undergrad degree, got a masters degree in European history from the sages of realpolitik at Yale. Boot has followed a typical pundit’s career track, with a stint at the Christian Science Monitor, followed by a post as the editorial features editor at the Wall Street Journal, where he supervises the production of bellicose propaganda from the (relative) safety of his office in downtown Manhattan. He lives with his family in Westchester County.
Boot’s academic and journalistic credentials are good, and his research and writing live up to the resume. But he has no apparent military experience. Unlike fellow journalists at top-tier papers, like columnist Tom Friedman or, say, correspondent Daniel Pearl, Boot doesn’t even seem to have notable international experience as journalist. This makes his avid enthusiasm for overseas wars rather suspect.
To be fair, I don’t have a strong counter argument to explain when the US should go to war. I’m not a pacifist — I think war is sometimes necessary, and justification for war is sometimes obvious. But I don’t have a coherent opinion about when and how often to fight. Boot has made a very persuasive case that “small wars” can be effective. But he hasn’t argued convincingly that the US should aggressively police the world. And despite the exciting narrative, there is plenty of other evidence that war isn’t quite as much fun as good war stories.

Just read two really cool

Just read two really cool books about recent scientific discoveries about the behavior of networks:
* Nexus, by Mark Buchanan, former editor of Nature magazine
* Linked, by Albert-Laslo Barabasi, one of the scientists whose team made some of the key discoveries
It’s a small world after all
There are many versions of the party game. The website, Six Degrees of Kevin Bacon, looks up the number of links connecting an arbitrary celebrity with Kevin Bacon. Will Smith was in Independence Day (1996) with Harry Connick, Jr., who was in My Dog Skip (2000) with Kevin Bacon. In another version of the party game, mathematicians boast of their “Erdos number” — how many close are they to a person who’s published a paper with Paul Erdos, the prolific and eccentric Hungarian mathematician. A variant called “Jewish geography” connects people via links through summer camps, social clubs and synagogues.
The intuitive insight that communities are “small worlds” has been quantified. Just in the last four years, scientists have developed models to describe the properties and behavior of “small-worlds” networks.
Networks can be characterized by several parameters:
* the level of clustering — how connected a given node is to nearby nodes. For example, social networks are highly clustered — one’s friends are likely to know each other
* the degree of separation, also called the diameter — how many links it takes on average to get from one node to another
* the level of hierarchy — how similar is the level of connectivity among different nodes. Do most nodes have about the same level of connection, or are some nodes much more connected than others?
A network can become “a small world” in one of two ways:
* a small number of long-distance connections. If you take a network where most connections are local, and add just a few long-distance connections, the network quickly “links up”, making it possible to traverse vast distances in just a few hops. For example, a coffee trader in Guatemala provides a link connecting a rural coffee growing family to an urban latte-sipper in just a few steps. Research by Duncan Watts and Steven Strogatz, published in 1998, modeled the role of long-distance connections in creating the “small world” effect.
* a small number of big hubs. On the worldwide web, the Yahoo news portal has lots of links to local news sites, making it easy to find local news in many of the world’s languages in just a few clicks. This type of network, in which a few members of a set have most links, and many members have few links, are called “scale free networks”, and can be described by a power law plotting the distribution of links among nodes. Research by Barabasi and his team, published in 1999 and more recently, modeled this pattern and found evidence of it in a variety of domains.
The “small worlds” patterns create networks that are highly resilient, yet vulnerable to certain kinds of failure.
* small worlds networks are invulnerable to random damage — if you randomly remove nodes from the internet, or species from an ecosystem, the system will continue to operate with little disturbance
* small worlds networks are vulnerable to attacks on connectors or hubs — if you take down a number of key internet hubs, or remove just a few linchpin species in ecosystem, the connections in the system will break down.
With the “small worlds” model in hand, scientists foraged for data sets and mapped the workings of small-worlds networks in a wide variety of domains:
* the web, which can be traversed with a few hyperlinks
* the internet — which can be crossed in a few hops
* electric power networks
* social networks
* ecosystems, in which a few “hub” species are predators or prey for many others.
* biochemistry — in which a few key chemicals catalyze many reactions.
* group behavior — in which fireflies start blinking in unison, and theater-goers unconsiously synchronize their applause
Relationship to other aspects of complexity theory
One of the fun things about reading the books is drawing relationships between “small worlds networks” and other aspects of complex, emergent systems, although these links are not well-developed in the books themselves.
Stuart Kauffman, a theoretical biologist, has developed a set of models to explain the natural emergence of order in open thermodyamic systems. According to Kauffman’s models, explained in his book, “At Home in the Universe”,
* self-replication is likely to emerge from a set of sufficiently diverse chemicals in high concentration
* genes code for a relatively small number of types of cells because of the network parameters of gene expression (Kauffman theorizes that it is the low coupling parameter that makes the state space of gene expression much lower than one might expect).
* the evolution of species can be modeled by adaptive walks across “fitness landscapes”, in which organisms with better-adapted traits outcompete others, and produce descendants with the opportunity to become even more fit. Key parameters of the model include the level of randomness within the fitness landscape (in a random landscape, a small change in an organism would cause a big change in fitness; in a non-random landscape, a small change in an organism would probably cause a small change in fitness); the level of coupling among genes in an organism (this models conflicting constraints — e.g. a gene that protects against malaria also increases vulnerability to blood disease); and the level of coupling among species in the landscape. In these models, extinctions follow a “power law” distribution, with frequent extinctions of small numbers of species, and infrequent catastrophes wiping out many species at once.
Kaufman’s theories about the emergence of organization and the mechanisms of evolution are fascinating and appealing. But in the absence of any but the sketchiest of empirical evidence, his work is vulnerable to criticism that it’s computer art — the properties of his models could just be artifacts of the parameters plugged into the models.
The empirical data analyzed by Barabasi’s team about chemical reaction networks and connection patterns in ecosystems seem like early evidence that nature works in the ways that Kauffman describes. Networks such as ecosystems and the world wide web have a small number of key nodes with many connections, and a great many nodes with fewer connections. According to the network model, this will lead to an evolutionary pattern with many small extinctions of non-hub species, and some mass disasters when key species are taken eliminated.
The Watts and Barabasi research suggests some alternate ways to configure Kaufman’s model, creating similar results with data that fit more closely with empirical evidence.
* Kauffman’s model accounts for long evolutionary jumps — the probability that a small change in an organism results in a large change in fitness — by tuning the “randomness” of the fitness landscape. Watts’ use a seemingly simpler to achieve similar results, by adding just a few nodes with long-distance coupbling behavior.
* Kaufman’s model tunes the average level of coupling up and down, reaching realistic behavior at a particular range of parameters. Barabasi’s model observes that level of coupling in a network varies by power law, and this distribution predicts the observed behavior.
Much more evidence is needed to confirm or disprove Kaufman’s theories, and to refine the models, in networks of gene expression; ecological networks, and evolution. The ongoing research and analysis models seems like it is on the right track to find these things out.
One of the key insights of Barabasi’s team is that a “scale-free network” can be created by a simple growth pattern — if new nodes add links with slight preference for popular nodes, the hierarchical pattern will emerge. It would be interesting to see future research that looked in more detail at models of evolution and growth.
In particular, the Watts and Barabasi models focus on patterns of network wiring — the number and distance of linkes. There are additional interesting questions about what this network architecture means with respect to the level of influence between nodes. What is the relationship between the architecture of the network and the way the network is used to transmit information?
That’s one of the most exciting things about studying this topic — the work is not near done.
The unfinished nature of the field shows up in some logical gaps in the books.
Both books explain how network growth patterns enable the rich to get richer, but that does not seem to me to be the most interesting part of the story. It is true that wealthy investors make more money, and really big sites like Yahoo and Amazon acquire the most links.
But the Pareto principle doesn’t explain whether and how the poor get rich. Google comes from nowhere, provides a better search engine, and rapidly emerges as the leading search site. And the Pareto principle doesn’t talk about impact of providing “small-worlds” connectivity to the remote and obscure. The interesting thing about the web is not that Yahoo is popular – it’s that a quick keyword search will find sites on medieval theologians and African cooking, and a couple of clicks on Yahoo News links will get you local media in Farsi.
Also, neither book has a strong discussion about limits to network growth, or differentiates between hub systems with obvious physical limits, like airports, and with few physical limits, like the information space of the web.
Comparison and contrast
The books are eerily similar, as if one of of the writers was looking over the other one’s shoulder as he wrote. The similarity in substance is not that surpising — after all, the books explain the same papers by the same set of scientists over a few year period of time. What is odder is that the books contain many of the same anecdotes — tales of Erdos, the eccentric Hungarian mathematician; the inspiration of Duncan Watts by synchronized fireflies, the creation of the Oracle of Kevin Bacon. Both books very similar sections on the internet and network economy, with a similar sweeping generalizations about impending change, and similar lack of substance.
Buchanan is a professional writer, and the book is a little better written. His magazine instincts show — each chapter is nicely structured, starting with anecdotes about people, and uncovering some new theme. The book does a decent job with transitions — it reads like a book rather than a collection of articles. Buchanan has a PhD in physics — he’s read the primary sources, he understands the math, he enjoys the subject and he doesn’t pander to the audience.
Barabasi is a participant, not a bystander — the unique strength of the book lies in the first-hand stories of his team and their discoveries. Barabasi is proud of his achievements; he makes it very clear that the topic was not properly understood until his team started their work. A typical sentence along these lines: “Uncovering and explaining these laws has been a fascinating roller coaster ride during which we have learned more about our complex, interconnected world than was known in the last hundred years.” This is not the place to look for humility.
Both books were definitely worth reading, with clear explanations, great references to the sources, and a lot of food for thought. It is quite a thrill to read about these developments as they are happening.

Computational Beauty of Nature, by

Computational Beauty of Nature, by Gary Flake, is a very nicely written walk through topics related to chaos and complexity, including fractals, chaos, artificial life, adaptive systems, and neural networks. This is THE one book for folks who want to dive into these topics one level deeper than the popular science books. Each chapter has references to the primary source books and articles, if you want to pursue the topics in greater depth.
The book’s website has a set of Java applets and C programs to run the simulations — for example, you can play with the parameters of L-System fractals to simulate different kinds of plant shapes. The source code is available to download and play with.
Flake does a lovely job of explaining the math and modeling concepts, in a manner that is comprehensible to those of us without extensive math backgrounds. Sometimes his one-page intros go a bit fast for me, but it’s easy enough to hit Google, find a relevant tutorial, then go back and finish the chapter. I needed to do this for the sections on matrix math and circuit design — this is a very pleasurable way to learn.