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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.
While A New Kind of Science may have lots of pretty pictures, and may be a decent survey of the field of cellular automata and its potential applications, and while Stephen Wolfram is no doubt a smart man, the quality of the book is overshadowed by his pathetically arrogant writing, wherein he pratically claims credit for CA, despite actually doing very little to even further the field. It's sad that people are beginning to think he really is a leader in the study. Please dissociate Wolfram and CA in your mind. Thanks...
.. we kind of knew already that complexity can be acheived with a basic set of rules re flocking. This may be interesting, but its hardly new.
Sounds like they are rehashing old ideas into a book just in time for Xmas to get you to splash your cash.
"So there he is, risen from the dead. Like that fella, E. T." - Father Ted Crilly
but isn't this terrain Douglas Hofstadter covered about twenty-five years ago in Gödel, Escher, Bach? Does Johnson's book say much new? Has a quarter-century's "progress" in CA and AI brought us any closer to singularity? And will I ever stop posting this comment in rhetorical question form?
Welcome to the Panopticon. Used to be a prison, now it's your home.
The whole point of this field is that no such connection is needed, complex behavior can arrise from simple things.
No, no it's not. Now go find a sci-fi thread somewhere.
Kind of like the continuum going from observing at the atomic level to observing at the macroscopic level. The physics of the atomic level is VERY different then the physics of the macroscopic level. Understandably, when you get to a point where you can't use one model over the other, things can get pretty hairy.
Can you say that the atomic level CAUSES the macroscopic level, i.e. one level emerges out of the other? My feeling is, it doesn't make much of a difference. The interactions you get depend upon your level of observation- they don't necessarily depend on what the interactions are at a different level. Observing at both levels is useful for different reasons. For example, for most low-speed aerodynamics, the model of air that you use is streamlines in the flow. For this situation and it's goals, it doesn't much matter to the airplane what is going on at the atomic level. The airplane is on a macroscopic level, so what matters is the physics of the macroscopic level. You fit the model to the same level and dementions of the thing you're observing. Remember calculus and limits? The limit works because it creates a fundmental building block of experience in a relavant dimension. Ex: dt is an infinitely small measure of a direction in time. But time is relevant in the demensions of the thing you're observing (actions the real world), so it's useful for the theory about the real world you want to create.
Due to my study on how people work, and that there are fundamental principles of human interaction that apply regardless of the individual person, I think it's probable that they're are fundmental principles of the overall interactions of an ant colony (we may not know them yet, but they are there). It's just that if you observe the colony at the microscopic level, you may not find them, since you're looking in the wrong place. Chaos Theory shows that even when behavior appears random, there are principles which create the randomness.
I guess it's nice these people have their "new" science to investigate- emergence. Hey, if it creates some new thought and gets people interested, I'm all for it. But I don't think that one thing is emerging out of another: it's just observing that for this particular level of observation, traits that were appearent at other levels have a bearing on the problem.
It's all the same thing, just different levels with different rules. (For example, duality is pretty much a law in the universe. You can't really equate the things that compose the duality, you can only recognize that the duality exists.)