I agree that this is a really interesting question. A couple of half-baked thoughts:
Alicorn’s formulation here is basically a search algorithm. The first two stages (Saturation and Distillation) are ways of using existing information to find decent initial values; the final stage (Experimentation) is the stepping algorithm. Thinking about it this way, it’s immediately obvious that there’s a lot more that could go into this last part: how to carve up the search space, how to decide which direction to step, whether to accept a step, etc. all of which have been explored extensively in other contexts. (Note: I’m not suggesting that this makes the problem trivial, or we should just think about this in terms of existing search algorithm paradigms; merely that thinking about things in this way could provide useful insights.)
One interesting facet of this sort of problem is that the precise mode of “failure” of a particular experiment can give information about where to step next. At a very basic level, you have things like burning, which, as most people will realize, suggest cooking at a lower temperature or for less time. At a higher level, you have things like the failure to form peaks, which, unless you can get more information from elsewhere, or you have a good understanding of food chemistry, you probably won’t have much of an idea how to fix.
I agree that this is a really interesting question. A couple of half-baked thoughts:
Alicorn’s formulation here is basically a search algorithm. The first two stages (Saturation and Distillation) are ways of using existing information to find decent initial values; the final stage (Experimentation) is the stepping algorithm. Thinking about it this way, it’s immediately obvious that there’s a lot more that could go into this last part: how to carve up the search space, how to decide which direction to step, whether to accept a step, etc. all of which have been explored extensively in other contexts. (Note: I’m not suggesting that this makes the problem trivial, or we should just think about this in terms of existing search algorithm paradigms; merely that thinking about things in this way could provide useful insights.)
One interesting facet of this sort of problem is that the precise mode of “failure” of a particular experiment can give information about where to step next. At a very basic level, you have things like burning, which, as most people will realize, suggest cooking at a lower temperature or for less time. At a higher level, you have things like the failure to form peaks, which, unless you can get more information from elsewhere, or you have a good understanding of food chemistry, you probably won’t have much of an idea how to fix.