ISSN:
1614-7456
Source:
Springer Online Journal Archives 1860-2000
Topics:
Computer Science
Notes:
Abstract By their very nature, complex systems resist analysis by decomposition. It is just not possible to study, say, the human immune system or a stock market, by breaking it up into individual parts—molecules or traders-and looking at what these parts do in isolation. The very essence of the system lies in the interaction among all its parts, with the overall behavior of the system emerging from these interactions. So by throwing away the interactions, one also throws away any hope of actually understanding the workings of the system. The problem is that until very recently, there was no way of studying these sorts of systems as complete entities, since to do experiments with stock markets, immune systems, rainforest ecosystems, and the like was either too expensive, too dangerous, or just plain too difficult. But the arrival of cheap, powerful, widespread computing capability over the past decade or so has changed the situation entirely. This paper will examine the way in which the ability to create surrogate versions of real complex systems inside our computing machines changes the way we do science. In particular, emphasis will be laid upon the idea that these so-called, “artificial worlds” play the role of laboratories for complex systems, laboratories that are completely analogous to the more familiar laboratories that have been used by physicists, biologists, and chemists for centuries to understand the workings of matter. Now, however, we have laboratories that allow us to explore information instead of matter. Because the ability to do controlled, repeatable experiments is a necessary precondition to the creation of a scientific theory of anything, the argument will be made that, for perhaps the first time in history, we are now in a position to think realistically about the creation of a theory of complex systems. These philosophical points will be illustrated by ongoing work with artificial road-traffic networks, as well as with systems for studying social and cultural phenomena.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF02471105
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