Re:Gigerenzer’s simple rules of thumb often outperform compl...
by cwillu on Wednesday March 03, 2021 @08:22AM
(#26327932)
Is this a fair restatement: “Models (and systems) that accurately reflect reality with a high fidelity due in part to their accurate assignment of values to a larger number of parameters are fragile”?
I agree that that's true, but my point (and I think part of what the article is saying) is that most “optimized” systems/models are not in fact doing that. In which case, the point I'd take (if I read you correctly) is that even once you _have_ managed to accurately set the parameters (which is harder to do and validate than it looks), you still have a fragile model/system.
Alternatively [edited to add]:
Define a model as a system that is attempting to match another system in behaviour. And so now you have two problems:
① a complicated model is itself fragile (by analogy to the system it's modelling)
② a complicated system has more ways to diverge from the system it's trying to model
Hmm, in which case it's kinda the same thing after all, except one is about making the model in the first place, and the other is maintaining it, maybe?
I agree that that's true, but my point (and I think part of what the article is saying) is that most “optimized” systems/models are not in fact doing that. In which case, the point I'd take (if I read you correctly) is that even once you _have_ managed to accurately set the parameters (which is harder to do and validate than it looks), you still have a fragile model/system.
Alternatively [edited to add]:
Define a model as a system that is attempting to match another system in behaviour. And so now you have two problems: ① a complicated model is itself fragile (by analogy to the system it's modelling) ② a complicated system has more ways to diverge from the system it's trying to model
Hmm, in which case it's kinda the same thing after all, except one is about making the model in the first place, and the other is maintaining it, maybe?