Complexity:
The Emerging Science at the Edge of Order and Chaos
by M. M. Waldrop
1992, Simon &
Schuster, New York, NY
ABSTRACT -
The stories of a few of the leading contributors (economist Brian Arthur,
biologist Stuart Kauffman, computer scientist Chris Langton) to the new science of complexity
are nicely told. These contributors come from a variety of disciplines and have come together
through the Santa Fe Institute.
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Key
Points:
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- All complex systems are built up from numerous
components which
constantly drive large and small scale change, through common
mechanisms, in the overall system.
- The mutual dance of interdependence among
organisms is stressed as is
the growing recognition of the central role of cooperation in fostering
survival as contrasted with reliance on competition.
- Complex systems seem to operate and survive
best when they operate
on the edge of chaos and order and when behavior is organized from
the bottom up.
To effect a systems
behavior or development one must appreciate its patterns
and power, apply interventions judiciously, and don’t bet on a limited set of
strategies.
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Master
of the Game
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Key Point:
All complex systems are built up from numerous components which
constantly drive large and small scale change, through common mechanisms, in
the overall system.
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- "Complex adaptive systems."...all
seemed to share certain crucial
properties...
- First...each of these systems is a network
of many ‘agents’ acting in
parallel...Furthermore...the control of a complex adaptive system tends
to be highly dispersed...If there is to be any coherent behavior in the
system, it has to arise from competition and cooperation among the
agents themselves...
- Second...a complex adaptive system has
many levels of organization,
with agents at any one level serving as the building blocks for agents at
a higher level...Furthermore, said Holland - and this was something he
considered very important - complex adaptive systems are constantly
revising and rearranging their building blocks as they gain
experience...At some deep, fundamental level, said Holland, all these
processes of learning, evolution, and adaptation are the same...
- Third...all complex adaptive systems anticipate
the future...
- Finally, said Holland, complex adaptive
systems typically have many
niches, each one of which can be exploited by an agent adapted to fill
that niche...Moreover, the very act of filling one niche opens up more
niches - for new parasites, for new predators and prey, for new
symbiotic partners. So new opportunities are always being created by
the system. And that, in turn, means that it’s essentially meaningless to
talk about a complex adaptive system being in equilibrium: the system
can never get there. It is always unfolding, always in transition. In fact, if
the system ever does reach equilibrium, it isn’t stable. It’s dead. And by
the same token,...there’s no point in imagining that the agents in the
system can ever "optimize" their fitness, or their utility...The space of
possibilities is too vast; they have no practical way of finding the
optimum. the most they can ever do is to change and improve
themselves relative to what the other agents are doing." p. 145-148
- What Holland wanted to know was how evolution
could explore this
immense space of possibilities and find useful combinations of genes -
without having to search over every square inch of territory...Indeed,
thought Holland, that’s what this business of "emergence" was all about:
building blocks at one level combining into new blocks at a higher level.
It seemed to be one of the fundamental organizing principles of the
world...Once a set of building blocks like this has been tweaked and
refined and thoroughly debugged through experience...then it can
generally be adapted and recombined to build a great many new
concepts....And that, in turn, suggests a whole new mechanism for
adaptation in general. Instead of moving through that immense space of
possibilities step by step, so to speak, an adaptive system can reshuffle
its building blocks and take giant steps." p. 167-170
"Reproduction
and crossover provided the mechanism for building blocks of
genes to emerge and evolve together - and, not incidentally, provided a
mechanism for a population of individuals to explore the space of possibilities
with impressive efficiency. By the mid - 1960s, in fact, Holland had proved
what he called this schema theorem, the fundamental theorem of genetic
algorithms: in the presence of reproduction, crossover, and mutation, almost any
compact cluster of genes that provides above-average fitness will grow in the
population exponentially." p. 174
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Peasants
Under Glass
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Key Point:
The mutual dance of interdependence among organisms is stressed
as is the growing recognition of the central role of cooperation in fostering
survival as contrasted with reliance on competition.
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- "Any given organism’s ability
to survive and reproduce depends on
what niche it is filling, what other organisms are around, what resources
it can gather, even what its past history has been. "That shift in
viewpoint is very important," says Holland. Indeed, evolutionary
biologists consider it so important that they’ve made up a special word
for it: organisms in an ecosystem don’t just evolve, they co-evolve.
Organisms don’t change by climbing uphill to the highest peak of some
abstract fitness landscape...(The fitness-maximizing organisms of
classical population genetics actually look a lot like the utility-maximizing
agents of neoclassical economics.) Real organisms constantly circle and
chase one another in an infinitely complex dance of co-evolution." p.
259
- ...he wanted to understand a deep paradox
in evolution: the fact that the
same relentless competition that gives rise to evolutionary arms races
can also give rise to symbiosis and other forms of cooperation...It was a
fundamental problem is evolutionary biology - not to mention
economics, political science, and all of human affairs. In a competitive
world, why do organisms cooperate at all? Why do they leave
themselves open to "allies" who could easily turn on them?" p. 262
In a computer simulation
game on competition versus cooperation, a tit for tat
strategy (seek cooperation with your competitor, if reciprocated, keep
cooperating; if cooperative approach is met by competition, compete back, if
approach changes to cooperation, reciprocate) beat all other strategies
repeatedly. "The conclusion was almost inescapable. Nice guys - or more
precisely, nice, forgiving, tough, and clear guys - can indeed finish first." p. 264
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Waiting
for Carnot
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Key Point: Complex
systems seem to operate and survive best when they
operate on the edge of chaos and order and when behavior is organized from
the bottom up.
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- "The most surprising lesson we have
learned from simulating complex
physical systems on computers is that complex behavior need not
have complex roots...Indeed, tremendously interesting and beguilingly
complex behavior can emerge from collections of extremely simple
components." p. 279
- "...the way to achieve lifelike behavior
is to simulate populations of
simple units instead of one big complex unit. Use local control instead of
global control. Let the behavior emerge from the bottom up, instead of
being specified from the top down. And while you’re at it, focus on
ongoing behavior instead of the final result." p. 280
"Living systems
are actually very close to this edge-of-chaos phase transition,
where things are much looser and more fluid. And natural selection is not the
antagonist of self-organization. It’s more like a law of motion - a force that is
constantly pushing emergent, self-organizing systems toward the edge of chaos."
p. 303
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Work
in Progress
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Key Point: To
effect a systems behavior or development one must appreciate
its patterns and power, apply interventions judiciously, and don’t bet on a
limited set of strategies.
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- "You can look at the complexity revolution
in almost theological terms,
he (Arthur) says. "The Newtonian clockwork metaphor is akin to
standard Protestantism. Basically there’s order in the universe...The
alternative - the complex approach - is total Taoist. In Taoism there is
no inherent order... The universe in Taoism is perceived as vast,
amorphous, and ever-changing... So we are part of this thing that is
never changing and always changing. If you think that you’re a
steamboat and can go up the river, you’re kidding yourself. Actually,
you’re just the captain of a paper boat drifting down the river. If you try
to resist, you’re not going to get anywhere. On the other hand, if you
quietly observe the flow, realizing that you’re part of it, realizing that the
flow is ever-changing and always leading to new complexities, then
every so often you can stick an oar into the river and punt yourself from
one eddy to another." "Notice that this is not a recipe for passivity, or
fatalism," says Arthur. "This is a powerful approach that makes use of
the natural nonlinear dynamics of the system. You apply available force
to the maximum effect... The idea is to observe, to act courageously,
and to pick your timing extremely well." p. 330 - 331
"What has
happened is that we’re beginning to lose our innocence, or naiveté,
about how the world works. As we begin to understand complex systems, we
begin to understand that we’re part of an ever- changing, interlocking, nonlinear,
kaleidoscopic world. So the question is how you maneuver in a world like that.
And the answer is that you want to keep as many options open as possible.
You go for viability, something that’s workable, rather than what’s ‘optimal.’
A
lot of people say to that, ‘Aren’t you than accepting second best?’ No, you’re
not, because optimization isn’t well-defined anymore. What you’re trying to do
is maximize robustness, or survivability, in the face of an ill-defined future." p.
333 - 334
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1. Thoughts
