Optimization vs. Adaptation

A word on optimization. This is feasible for static problem domains, like airplane wings, since the problem domain (laws of aerodynamics) doesn't change. In dynamic problem domains, such as traffic or societies, you can't really optimize, because the "optimum" is changing constantly (if it is knowable). In these circumstances, indeed the system tries to find the "best" solution for the current situation (optimize), but since the optimization process neither reaches an optimum nor stabilizes, it would be better described as an adaptation process. Like this you can understand why short term decisions lead to long term failures.

More on my paper: Self-Organizing Traffic Lights. Complex Systems 16(1): 29-53. [preprint]

Comments

Carlos said…
Answer to spec:

My gut feeling is that an adaptive market strategy would beat an optimizing one. Certainly, if you "optimize" your predictions every minute, this counts as adaptation...
However, if everybody would use adaptive strategies I wouldn't be able to say what would happen, but it would be terribly interesting to find out...
Carlos said…
Answer to spec:

I think that in principle you can use swarm optimization to approximate solutions continuously, but I'm not familiar with the literature.

If everybody used the same strategy, not necessarily they would reach a stale mate, since timing is also an important factor, e.g. the first or last trader might have a slight advantage that on the long run would lead to outperforming the other traders with the same strategy... also not all traders have the same resources, so usually a trader with more resources can outperform those with less...

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