Transcript A bit presumptuous? Introduction to Complex Systems: How to think like nature Unintended consequences: mechanism, function, and purpose Russ Abbott Sr.

A bit presumptuous?
Introduction to Complex Systems:
How to think like nature
Unintended consequences:
mechanism, function, and purpose
Russ Abbott
Sr. Engr. Spec.
Besides, does
nature really think?
310-336-1398
[email protected]
 1998-2007. The Aerospace Corporation. All Rights Reserved.
1
A fable
• Once upon a time, a state in India had too many snakes.
• To solve this problem the government instituted an incentivebased program to encourage its citizens to kill snakes.
• It created the No Snake Left Alive program.
– Anyone who brings a dead snake into a field office of the
Dead Snake Control Authority (DSCA) will be paid a
generous Dead Snake Bounty (DSB).
• A year later the DSB budget was exhausted. DSCA had paid
for a significant number of dead snakes.
• But there was no noticeable reduction in the number of
snakes plaguing the good citizens of the state.
• What went wrong?
2
The DSCA mechanism
Receive dead snake
certificate. Submit
certificate to DSCA.
DSCA
What would you do if
this mechanism were
available in your world?
Receive
money.
Start a
snake
farm.
Catch, kill, and submit
a dead snake.
Dead snake
verifier
3
Moral: unintended consequences
• The preceding is an example of what is sometimes called an
unintended consequence.
• It represents an entire category of (unintended and unexpected)
phenomena in which
– a mechanism is installed in an environment, but then
– the mechanism is used/exploited in unanticipated ways.
• Once a mechanism is installed in the environment, it will be
used for whatever purposes “users” can think to make of it …
– which may not be that for which it was originally intended.
That’s how
nature works.
The first lesson of complex systems thinking is
that one must always be aware of the relationship
between systems and their environments.
4
Parasites that control their hosts
• Dicrocoelium dendriticum causes host ants to
climb grass blades where they are eaten by
grazing animals, which is where D. dendriticum
lives out its adult life.
• Toxoplasma gondii cause mice not to fear cats,
which is where T. gondii reproduces.
• Spinochordodes tellinii causes host insects to
jump into the water and drown, where S. tellinii
grows to adulthood.
5
Follow the energy/money
• Energy (and its proxy money) is fundamental.
• Any mechanism that provides access to
energy/money/resources is a potential target
of unintended consequences.
• A niche: a way of extracting energy/money/
resources from an environment
• Example: power is supplied to computer USB ports
– Presumably to provide power for USB devices.
– The wifi bridge uses the Internet (not USB) Port to
transfer data.
– But it gets its power from the USB port.
6
Locomotion in E. coli
• [E. coli] movements consist of short straight runs, each
lasting a second or less, punctuated by briefer episodes of
random tumbling: each tumble reorients the cell and sets it
off in a new direction.
• Cells of E. coli are propelled by their flagella, four to ten
slender filaments that project from random sites on the cell’s
surface. … Despite their appearance and name (from the
Greek for whip), flagella do not lash; they rotate quite rigidly,
not unlike a ship’s propeller. …
• A cell … can rotate [its] flagellum either clockwise or
counter-clockwise. Runs and tumbles correspond to
opposite senses of rotation.
–
–
When the flagella turn counter-clockwise [as seen from behind] the individual filaments
coalesce into a helical bundle that rotates as a unit and thrusts the cell forward in a
smooth straight run. …
Frequently and randomly the sense of the rotation is abruptly reversed, the flagellar
bundle flies apart and the cell tumbles until the motor reverses once again.
Harold, Franklyn M. (2001) The Way of the Cell: Molecules,
Organisms, and the Order of Life, Oxford University Press.
7
Locomotion in E. coli
• Cells that are moving up the gradient of an attractant
… tumble less frequently than cells wandering in a
homogeneous medium: while cells moving away from
the source are more likely to tumble. In consequence,
cells take longer runs toward the source and shorter
ones away.
• How can a cell “know” whether it is traveling up the
gradient or down? It measures the attractant
concentration at the present instant and “compares” it
with that a few milliseconds ago.
• E. coli can respond within a millisecond to local
changes in concentration, and under optimal
conditions readily detects a gradient as shallow as
one part in a thousand over the length of a cell.
Franklin Harold, The Way of the Cell
8
Mechanism, function, and purpose*
• Mechanism: The results of physical
processes within an entity.
– The chemical reactions built into E.coli that result in its
flagella movements.
– The DSCA mechanism.
• Function: The effect of a mechanism on
the environment and on the relationship
between an entity and its environment.
– E. coli moves about. In particular, it moves up nutrient
gradients.
– Snakes are killed and delivered; money is exchanged.
Wikipedia Commons
• Purpose: The consequence for the entity of
the change in its environment or its
relationship with its environment.
– E. coli is better able to feed, which is necessary for
self-persistence.
– Snake farming is encouraged?
Socrates
*Compare to Measures of Performance, Effectiveness, and Utility
9
• NetLogo (http://ccl.northwestern.edu/netlogo/) describes itself as “a
cross-platform multi-agent programmable modeling environment …
for simulating natural and social phenomena.”
• It is produced by the Center for Connected Learning and ComputerBased Modeling at Northwestern University. (Uri Wilensky)
• It is intended primarily for education (high school, middle school
and even earlier) and for qualitative modeling.
– It is not a detailed modeling or analysis tool.
• It is implemented in Java.
• Version 4.0 was released September 2007.
• It’s free to download, but it’s not open source.
• It produces models that run both as applications and as applets.
• It has a large library of models, which also run as both applications
and applets, and which can be run directly from the website.
10
Let’s try it
File > Models Library > Biology > Ants
Click Open
11
Three tabs
Interface tab:
control the model.
To run most
models, press
setup and then
go.
Press go again to
stop the run.
Information tab:
documentation
about the model
Procedures tab:
the model in
NetLogo code
Online guide: http://ccl.northwestern.edu/netlogo/docs/
12
Simple ant foraging model
Ant rules
• If you are not carrying food,
• Move up the chemical-scent
gradient, if any.
• Pick up food, if any.
• Otherwise move randomly.
• If you are carrying food, move up
the nest-scent gradient. When you
reach the nest, deposit the food.
• population: number of ants
• diffusion-rate: rate at which the
chemical (pheromone) spreads
• evaporation-rate: rate at which
chemical evaporates
In “to look-for-food” procedure,
change “orange” to “blue”.
After running once, play around with
the population, diffusion-rate, and
evaporation-rate.
Turns plotting on/off.
Implemented chemically in real
ants, by software in NetLogo.
Can you get this picture, with paths to
all food sources simultaneously?
13
Two levels of emergence
Applications, e.g., email, IM, Wikipedia
• No individual chemical reaction inside the
WWW
(HTML) — for
browsers
+ servers
ants
is responsible
making
them follow
the rules that describe
their behavior.
Presentation
• That the internal Session
chemical reactions
together do is an
example of emergence.
Transport
• No individual rule
and no individual ant is
Network
responsible for the ant colony gathering
Physical
food.
• That the ants together bring about that
result is a second level of emergence.
Colony results
Ant behaviors
Ant chemistry
As we’ll see later, each
layer is called a
level of
abstraction
Notice the similarity to layered
communication protocols
14
Complex systems terms
• Emergence. A level of abstraction that can be described
independently of its implementation.
– Examples include the movement E. coli and ants through space toward a food
source, which can be described independently of how it is brought about.
• Multi-scalar. Applicable to systems that are understood
on multiple levels simultaneously, especially when a
lower level implements the emergence of some
functionality at a higher level.
– E. coli motion and ant foraging are both examples of multi-scalar systems.
Isn’t that true of
all systems?
System: a construct or collection of
different elements that together
produce results not obtainable by the
elements alone. — Eberhardt Rechtin
We are in the business of
producing emergence
Systems Architecting of Organizations:
Why Eagles Can't Swim, CRC, 1999.
15
Parasites that control their hosts
Details follow
16
One more—because it’s so famous
File > Models Library > Social Science > Segregation
Click Open
17
Credited with being the first agent-based model
• Reasonable micro-level preferences produce macro-level
segregation.
• Each agent wants the percentage of like agents to be as
indicated in %-similarity wanted.
– Similar agents/total agents. Empty neighbors ignored.
• Starts out at ~50% similar since scattered at random.
• But some are unhappy. They move to a random empty spot.
• Repeat until all agents happy.
• Easier to see if more agents. Set number to 2500 agents.
• 30%-similarity-wanted produces 75% similarity.
• 40%-similarity-wanted produces 80% similarity.
Try this.
• Set %-similarity-wanted to 75%. (Ethnic cleansing!)
• At about 2% unhappy, set it to 76%.
• Switch back and forth. An artifact of the model.
18
Lots of artifacts
• Counts only 8 neighbors.
• Can mitigate clustering (and produce stripes at
30%-similar-wanted) by adding one line.
to update-turtles
ask turtles [
;; in next two lines, we use "neighbors" to test the eight patches
;; surrounding the current patch
set similar-nearby count (turtles-on neighbors)
Want a separate slider
with [color = [color] of myself]
for %-other-wanted?
set other-nearby count (turtles-on neighbors)
with [color != [color] of myself]
set total-nearby similar-nearby + other-nearby
set happy? similar-nearby >= ( %-similar-wanted * total-nearby / 100 )
and other-nearby >= ( %-similar-wanted * total-nearby / 200 )
]
end
Sets non-similar requirement to be
half as many as similar requirement.
19
What to conclude from the segregation model?
• Models can illustrate mechanisms, e.g., for “selforganization” such as clusters and stripes.
• Models can offer insight but often do not provide
complete answers.
– What else do the agents want? Good schools,
safe neighborhoods? Etc.
– What do they really mean by “similar”? Etc.
• Models can be overly simple.
• Models can be manipulated.
20
Dicrocoelium dendriticum *
• D. dendriticum spends its adult life inside the liver of its
host. After mating, the eggs are excreted in the feces.
• The first intermediate host, the terrestrial snail (Cionella
lubrica in the United States), eats the feces, and
becomes infected by the larval parasites. … The snail
tries to defend itself by walling the parasites off in cysts,
which it then excretes and leaves behind in the grass.
• The second intermediate host, an ant (Formica fusca in
the United States) swallows a cyst loaded with hundreds
of juvenile lancet flukes. The parasites enter the gut and
then drift through its body. Some move to a cluster of
nerve cells where they take control of the ant's actions.
*
Text and image from Wikipedia.org.
• Every evening the infested ant climbs to the top of a
blade of grass until a grazing animal comes along and
eats the grass—and the ant and the fluke.
• The fluke grows to adulthood and lives out its life inside
the animal—where it reproduces, and the cycle
continues.
See also, Shelby Martin, “The Petri Dish: The journeys of the brainwashing parasite,” The Stanford Daily, April
20, 2007. http://daily.stanford.edu/article/2007/4/20/thePetriDishTheJourneysOfTheBrainwashingParasite
21
Toxoplasma gondii *
• The life cycle of T. gondii has two phases.
– The sexual part of the life cycle (coccidia
like) takes place only in members of the
Felidae family (domestic and wild cats).
– The asexual part of the life cycle can take
place in any warm-blooded animal.
• T. gondii infections have the ability to
change the behavior of rats and mice,
making them drawn to rather than fearful
of the scent of cats.
– This effect is advantageous to the
parasite, which will be able to sexually
reproduce if its host is eaten by a cat.
– The infection is almost surgical in its
precision, as it does not impact a rat's
other fears such as the fear of open
spaces or of unfamiliar smelling food.
*
Text and image from Wikipedia.org.
See also, Charles Q. Choi, “Bizarre Human Brain Parasite Precisely Alters Fear,”
Live Science, April 2, 2007. http://www.livescience.com/animals/070402_cat_urine.html
22
Spinochordodes tellinii *
• The nematomorph hairworm
Spinochordodes tellinii is a
parasitic worm whose larvae
develop in Orthopteran insects.
• When it is ready to leave the
host, the parasite causes the
host to jump into water, where
it drowns, but which returns the
parasite to the medium where
it grows to adulthood.
*
Text and image from Wikipedia.org.
See also, James Owen, “Suicide Grasshoppers Brainwashed by Parasite Worms,”
National Geographic News, September 1, 2005.
http://news.nationalgeographic.com/news/2005/09/0901_050901_wormparasite.html
23