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.
Try also John H Holland 'Hidden Order' and 'Emergence: From Chaos to Order'.
I read the first two chapters or so of that book. It's totally an essay strrrreeeetched into a book. Terribly boring (in a lite-on-content sort of way). On the topic of taking recommendations from Slashdot: A poster raved about "The Non-Designers Design Book," so I bought it. It's not completely worthless for total amateurs (like me), but it's pretty much written for the purpose of teaching secretaries how to make better-looking newsletters. Lesson learned.
Monstromart: Where shopping is a baffling ordeal
Seastead this.
I quoted this excellent book and gave some future directions about using the bottom-up Emergence technique when dealing with Threat Modeling. Read the last chapter in my MSc paper Threat Modeling for Web Applications using the STRIDE model Comments welcome. Thanks
Another good book on the subject of emergent systems is After Thought by James Baily. It is a quick and enjoyable read that takes a look at the evolution of mathematical and philosophical attempts at describing our universe from the ancient Greeks to modern day scientists. Specifically, he focuses on how we attempt to model the human brain electronically, and touches on parallel computing, cellular automata, genetic algorithms, and the techniques required to allow a machine to learn.
".. a rare blend of monster raving egomania and utter batshit insanity"
a r-automata.html
Cosma Rohilla Shalizi on S.Wolfram, A new kind of science
http://cscs.umich.edu/~crshalizi/notebooks/cellul
I found the following to be surprising and useful background for the glut of writing about complexity/emergence/universality etc. Lots of historical detail from J. S. Mill onwards about the use of emergence in philosophy. Good bibliography too of which I can recommend the Kaufman books as good fun:g ent/
http://plato.stanford.edu/entries/properties-emer
This seems like a fascinating book. I wrote a research paper on how local information leads to global coordination, and seems very relevant to the topics covered in the book. The idea is to take an array of nodes which are in one of two states. Each node can tell the state of only a few neighbors on either side. The idea is to find a cellular automata rule so that all states in the array converge to one state (this is known as the density classification task). This is the "local information can lead to global wisom" idea as stated in the review and is relevent to a score of biological and economic decentralized systems. I used genetic algorithms to solve this problem. I was a semi-finalist in the Siemens-Westinghouse contest and submitted the paper to the Intel Talent Search (yet to be judged). A pdf can be found at http://www.chem-phys.com/intel/alex.pdf
Make a wrapper program to create the playing field, instantiate as many 'agents' as you see fit, and let them loose. Tweak, rinse, repeat.
Better yet, use a simulation environment like breve and you get 3d rendering, collision detection, basic physics, and a lot more for free.
How to solve most of our problems: 1.Lots of nuclear plants. 2.Cure aging.
I have read the book, and that is not the impression that I, nor many other people who've read it, came away with. On the contrary, he repeatedly refers to it as his discovery- "...the new kind of science I [emphasis mine] have developed...", "...my discovery...", "...one of the more important single discoveries in the whole history of theoretical science..."
That's just in the first chapter, but it continues throughout. He makes little reference to others' work in the field, pretty much dismissing all work done prior to his becoming aware of the subject.
It is a good indicator of how lost in one's own world one is when none of the major peer-reviewed journals or scientific publishers is interested in "one of the more important single discoveries in the whole history of theoretical science". If a minor patent clerk can get his groundbreaking ideas out, one would hope an MacArthur award-winning, CalTech PhD-holding, Mathematica creator would be heard.
The whole book sounds to me like a guy who's been told how smart he was all his life, and is probably surrounded by sycophants, who has a lot of money and might have smoked a little too much weed.
It's okay, though, Stephen- the pictures are lovely.