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Introduction to Complex Systems: How to think like nature. A bit presumptuous?. Unintended consequences: mechanism, function, and purpose. Besides, does nature really think?. Russ Abbott Sr. Engr. Spec. 310-336-1398 Russ.Abbott@Aero.org.
A bit presumptuous?
Unintended consequences: mechanism, function, and purpose
Besides, does nature really think?
Sr. Engr. Spec.
The first lesson of complex systems thinking is that one must always be aware of the relationship between systems and their environments.
That’s how nature works.
Harold, Franklyn M. (2001) The Way of the Cell: Molecules, Organisms, and the Order of Life, Oxford University Press.
Franklin Harold, The Way of the Cell
*Compare to Measures of Performance, Effectiveness, and Utility
File > Models Library > Biology > Ants
Interface tab:control the model.
To run most models, press setup and then go. Press goagain to stop the run.
Informationtab:documentation about the model
Procedurestab:the model in NetLogo code
Online guide: http://ccl.northwestern.edu/netlogo/docs/
Turns plotting on/off.
In “tolook-for-food” procedure, change “orange” to “blue”.
Implemented chemically in real ants, by software in NetLogo.
After running once, play around with the population, diffusion-rate, and evaporation-rate.
Can you get this picture, with paths to all food sources simultaneously?
WWW (HTML) — browsers + servers
PhysicalTwo levels of emergence
As we’ll see later, each layer is called a level of abstraction
Notice the similarity to layered communication protocols
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.
System: a construct or collection of different elements that together produce results not obtainable by the elements alone. — Eberhardt Rechtin
Systems Architecting of Organizations: Why Eagles Can't Swim, CRC, 1999.
We are in the business of producing emergence
File > Models Library > Social Science > Segregation
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.
Counts only 8 neighbors.
Can mitigate clustering (and produce stripes at 30%-similar-wanted) by adding one line.
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)
with [color = [color] of myself]
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 )
Sets non-similar requirement to be half as many as similar requirement.
Want a separate slider for %-other-wanted?
Models can illustrate mechanisms, e.g., for “self-organization” 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.
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.
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.
* Text and image from Wikipedia.org.Dicrocoelium dendriticum *
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
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.Toxoplasma gondii *
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
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