Showing Web View For Page 367 | Show full page with images

in the majority of cases the best evidence that some particular set of effects are in fact the important ones ultimately comes just from the success of models that are based on these effects.

The systems that I discuss in this chapter are mostly complicated enough that there are at least tens of quite different effects that could contribute to their overall behavior. But in trying to construct the simplest possible models, I have always picked out just a few effects that I believe will be the most important. Inevitably there will be phenomena that depend on other effects, and which are therefore not correctly reproduced by the models I consider. So if these phenomena are crucial to some particular application, then there will be no choice but to extend the model for that application.

But insofar as the goal is to understand the basic mechanisms that are responsible for the most obvious features of overall behavior, it is important to keep the underlying model as simple as possible. For even with just a few extensions models usually become so complicated that it is almost impossible to tell where any particular feature of behavior really comes from.

Over the years I have been able to watch the progress of perhaps a dozen significant models that I have constructed—though in most cases never published—for a variety of kinds of systems with complex behavior. My original models have typically been extremely simple. And the initial response to them has usually been great surprise that such simple models could ever yield behavior that has even roughly the right features. But experts in the particular types of systems involved have usually been quick to point out that there are many details that my models do not correctly reproduce.

Then after an initial period where the models are often said to be too simplistic to be worth considering, there begin to be all sorts of extensions added that attempt to capture more effects and more details. The result of this is that after a few years my original models have evolved into models that are almost unrecognizably complex. But these models have often then been used with great success for many practical purposes. And at that point, with their success established, it sometimes happens that the models are examined more carefully—and

in the majority of cases the best evidence that some particular set of effects are in fact the important ones ultimately comes just from the success of models that are based on these effects.

The systems that I discuss in this chapter are mostly complicated enough that there are at least tens of quite different effects that could contribute to their overall behavior. But in trying to construct the simplest possible models, I have always picked out just a few effects that I believe will be the most important. Inevitably there will be phenomena that depend on other effects, and which are therefore not correctly reproduced by the models I consider. So if these phenomena are crucial to some particular application, then there will be no choice but to extend the model for that application.

But insofar as the goal is to understand the basic mechanisms that are responsible for the most obvious features of overall behavior, it is important to keep the underlying model as simple as possible. For even with just a few extensions models usually become so complicated that it is almost impossible to tell where any particular feature of behavior really comes from.

Over the years I have been able to watch the progress of perhaps a dozen significant models that I have constructed—though in most cases never published—for a variety of kinds of systems with complex behavior. My original models have typically been extremely simple. And the initial response to them has usually been great surprise that such simple models could ever yield behavior that has even roughly the right features. But experts in the particular types of systems involved have usually been quick to point out that there are many details that my models do not correctly reproduce.

Then after an initial period where the models are often said to be too simplistic to be worth considering, there begin to be all sorts of extensions added that attempt to capture more effects and more details. The result of this is that after a few years my original models have evolved into models that are almost unrecognizably complex. But these models have often then been used with great success for many practical purposes. And at that point, with their success established, it sometimes happens that the models are examined more carefully—and


Exportable Images for This Page:

From Stephen Wolfram: A New Kind of Science [citation]