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Emergence
The author makes a point that there are 3 main camps of scientific study.
- The study of simple systems - under a few dozen variables, like electromagnetism, or celestial mechanics.
- The study of stochastic systems - few million to few billion variables, like actuarial sciences and genetics.
- The study of disorganized complexity. Systems in the middle between a dozen and a few million variables, where the second order characteristics - how they interact, is of primary concern.
Deduction and induction work for the first two camps, but for the third, the interactions cause actions and reactions which are what scientists politely call counter intuitive, meaning your first thought is Huh? Or, in other words, it behaves quite differently from what your instincts and (so-called) common sense would tell you.
There are five basic principles for developing a system (or simulation of one) which can express emergent behavior:
- More is different. You get a very different behavior of the system when certain thresholds are reached.
- Ignorance is useful. Ants communicate with a vocabulary of around 20 words/ideas.
- Encourage random encounters. Much of the behavior of an ant colony comes from them just bumping into each other (or external things like food, or my foot).
- Look for patterns in the signs. Even with the limited vocabulary of ants, they can also express things based on the decay in the pheromones they deposit.
- Pay attention to your neighbors. Also described as "local information can lead to global wisdom."
One of the enduring myths we have, is that of the Ant Queen. The myth supposes that there is some central planning done in an ant colony. Instead, the queen exists only to pop eggs out. Male ants have such short lives, that in most species of ants, they have no mouths to eat with; they just don't live long enough to get hungry. The production of warriors and workers is stimulated by pheromones in the colony. Information on where to gather food is gathered through random acts of bumping into things. There is no ant which tells another to go lift that bale or tote that barge. It appears that our intelligence is a by-product of the neural interactions of our brains.
The economist Jane Jacobs had been studying things like this for years, and has been demonized by the majority of economists: they want to believe in some centralized controlling force, control that force, and you control the development of your economic system. People reading her books tend to think she worships sidewalks, instead, she values the communication that can only happen on sidewalks; people meeting each other and exchanging words. You can't say "hi" to your neighbors if you are each zipping past each other on the freeway.
One can experiment with emergent behavior with some software tools. The author explains a few, of which you are most likely to have experience with SimCity.
The main difference between chaos theory and emergent behavior theory lies in a couple important differences. A chaotic system has a number of determinable feedback loops, all of which are (usually critically) dependent upon the starting conditions. Emergent behavior has more to do with feedback loops causing totally different behavior, and when some threshold (usually population) is passed, the nature of the system drastically changes.
If you are looking for sample code to simulate things, you won't find it in this book. If, however, you want to get an overview of where this field is coming from, read this book.
You can purchase Emergence: the Connected lives of Ants, Brains, Cities and Software from bn.com. Slashdot welcomes readers' book reviews -- to see your own review here, carefully read the book review guidelines, then visit the submission page.
The thing is, there's no reason to be scared of autonomous organization - it is literally everywhere around us.
Swarming/flocking/schooling algorithms are a great example of this. All it takes is a desire to be close to your neighbors but not too close, and the swarm/flock/school functions largely on its own - it can even go around obstacles and re-merge, it optimizes into aerodynamic shapes, etc.
I love complexity from simplicity. One of my favorites occurs from the standard predator/prey population equation. If you run it for a while, it switches into repeating cycles of population size. However, the positions and numbers of cycles are dependant on the equation conditions. If you plot the cycles vs. the starting conditions, you get this beautiful graph of the data starting at a single point, then branching, and again, faster and faster until it forms into pure chaos... and then from the chaos, emerges three clean branches, which then fall to chaos again.
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This is, indeed, an interesting book and the reviewer fails to point out that Emergence goes into detail concerning the karma, moderation and meta-moderation system of this here web site.
:-) Towards the end where he's talking about emergent video games I got a little bored, but definitely a book that got me thinking. Worth reading even if you are aware of the way ants behave, because you probably don't know as much about slime mold as you should.
Author seems to think taco is a genius or something, but it's still a good read
John.
...but interesting, nonetheless. For two viewpoints that are more or less opposing, read Daniel Dennett and John Searle - the latter of whom is a latter-day dualist who talks a lot about emergence, aka emergent properties. Dennett thinks machines will be able to think, Searle doubts it.
I actually quite enjoyed this book. The stuff in there about the emergence of communities and trading groups in cities as a result of simple motivations was really interesting, and got me thinking about this for a while. The way in which simple interactions within an ant colony result in complex higher level behaviours such as cemetries and food distribution are also quite amazing!
However, it wasn't until I read Mitch Resnick's 'Turtles, Termites and Traffic Jams' that emergence and self organisation really clicked for me. Resnick basically developed a scripting language and an environment for investigating emergence in biological systems (termites, turtles, ants) and social systems such as traffic patterns and communities. The system is called StarLogo, and is well worth googling for.
This was also a theme from the Matrix. The machine world was not controlled by a single overlord but was instead made up of billions of different programs. All the way down to the "wind" or the "bird" programs. Taken individually they're all rather simple and pointless, but when taken as a whole they build something much more valuable.
but isn't this terrain Douglas Hofstadter covered about twenty-five years ago in Gödel, Escher, Bach?
:)
Exactly what I was thinking. I may have to read this book just for that comparison alone. For those who have not read it, I highly recommend it...it's not a weekend browser, but has some fascinating insight and thought experimentation. One of the most interesting books I've ever read. And the kind of books I usually like have more pictures than words
teeker
The essential concept is that each individual is a simple agent that operates autonomously, and makes very few very simple decisions as it goes about its work. The behaviour of one individual is unremarkable, but the behaviour that emerges from a large group of the same individuals is really quite amazing.
Because the concepts are really quite logically simple, this stuff is really simple to program too. Just fire up perl or java or any language that has a similar capability to OO concepts, write a simple object - your agent - that behaves according to a simple set of rules and responds in defined ways to certain stimuli. Make a wrapper program to create the playing field, instantiate as many 'agents' as you see fit, and let them loose. Tweak, rinse, repeat.
As an aside, when I was writing a simulation to emulate the behaviour of ants foraging (more to prove that perl and java were suitable languages for the task than to demonstrate anything new with ants per se), I went off and RTFM'ed quite a bit on ants. They're very interesting little critters in their own right. I picked the eyes out of the various behaviours of a bunch of different species of ants to come up with one that made a fun simulation (refer references below).
The bare mechanical simplicity with which some of these critters operate is really quite amazing. Take, for example, the concept of trail laying. I guess it's pretty widely known that many species of ants lay trails from food sources back to the nest to guide other ants to the food. (Try: find a line of ants climbing up the wall in the kitchen or somewhere, moisten your finger, wipe straight through the line (washing off the trail). They'll be all disoriented for a little while, but they'll quickly re-establish the trail, largely by random search). Anyhoo, what's really quite cool is how one species does it. The trail is just an emission from the back end of the ant that wipes along the ground as it walks. The mechanics are such that if the ant has a full crop, it puts pressure on the digestive tract, and forces stuff out the back. If its only lightly fed, it only forces a bit out the back, if its had a big feed, it forces a lot out the back and lays a denser trail. The outcome is that the ants lay stronger trails to the better food sources. Elegant, isn't it!
I could go on forever, but I won't. Some references below. Another behaviour that is probably even more interesting than trail laying is navigation. They're absolutely amazing. Various ants use various combinations of reference to the sun, counting the amount of ground that passes underneath them as they walk *AND* remembering turns!!!, and reference to major landmarks as they travel. Did I say amazing?
Anyhoo, here's a bunch of references on ant behaviour if anyone's interesting.
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