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> We therefore conclude that theoretically motivated experiment choice is potentially damaging for science, but in a way that will not be apparent to the scient
by gus_massa 9mo ago
> We therefore conclude that theoretically motivated experiment choice is potentially damaging for science, but in a way that will not be apparent to the scientists themselves.
They are analyzing a toy model of science. The details and in figure 1. They have a search space that has a few Gaussians like
f(x,y,z) = A0 * expt(-(x-x0)^2-(y-y0)^2-(z-z0)^2) + A1 * expt(-(x-x1)^2-(y-y1)^2-(z-z1)^2)
but maybe in more than 3 dimensions and maybe with more than 2 Gaussians.
They want the agents to find all of Gaussians.
It's somewhat similar to a maximization problem that is easier. There are many strategies for this, from gradient ascent to random sampling to a million more of variants. I like simulated annealing.
They claim that the best method is random sampling, that only work when the search space is small. But it breaks quite fast for high dimensional problems, unless the Gaussians are so big that cover most of the space, and perhaps I'm beeing too optimistic. Add noise, overlapping Gaussians and the problem gets super hard.
Let's get to a realistic example, all the molecules with 6 Carbons and 12 Hydrogens. Let's try to find all of them and their stables 3D configuration. This is chemistry from the first year in the university, perhaps earlier, no cutting edge science.
You have 18 atoms, so 18 * 3 = 54 dimensions, and the surface of -energy has a lot of mountains ranges and nasty stuff. Most of them very sharp. Let's try to find the local points of maximal -energy, that is much easier than the full map. These are the stable molecules, that (usually) have names.
* There is a cycle one with 6 Carbons, where each Carbon has 2 Hydrogens, https://en.wikipedia.org/wiki/Cyclohexane https://en.wikipedia.org/wiki/Cyclohexane Note that it actually has two different 3D variants.
* There is one with a cycle of 5 Carbons and 1 carbon attached to the cycle https://en.wikipedia.org/wiki/Methylcyclopentane https://en.wikipedia.org/wiki/Methylcyclopentane
* There are variants with shorter cycles, but I'm not sure how stable they are and Wikipedia has no page for them.
* There is also 3 linear versions, where the 6 Carbons are a s wavy line, and there is a double bound in one of the steps https://en.wikipedia.org/wiki/1-Hexene https://en.wikipedia.org/wiki/1-Hexene I'm not sure why the other two version have no page in Wikipedia, I think they should be stable, but sometimes it's not a local maximum or the local maximum is to shallow and the double bound jump and the Hydrogen reorganize.
* And there may be other nasty stuff, take a look at the complete list https://en.wikipedia.org/wiki/C6H12 https://en.wikipedia.org/wiki/C6H12.
And don't try to make the complete list when of molecules that includes a few Nitrogen, because the number of molecules explodes exponentially.
So this random sampling method they propose, does not even work for an elementary Chemistry problem.
- Eisenstein 9mo agoThey address this specifically and hand-wave it away: Moreover, both random and all other experimentation strategies we examined require constructing a bounded experimental space, a challenge that lies beyond the scope of the current work (see Almaatouq et al., 2024, for further discussion). I think their conclusion is still important to consider, though. It makes a point beyond the practicalities and more towards the philosophy of approach.
- gus_massa 9mo agoThat is an unrelated problem, that usually is not even a problem. For molecules, 10 Armstrong away is probably as good as infinite. For how many bananas should you eat per week to become the chess world champion, you can ask Wolfram Alpha to convert 2400kcal * 7 to bananas and get an upper bound. I think everyone agree that with infinite time a resources a brute force search is better in case there is a weird combination. But for finite time and resources you need to select a better strategy unless the search space is ridiculous small and smooth.
- Eisenstein 9mo agoI guess I am not following very well -- what exactly is an unrelated problem? Setting a bounded space?
- gus_massa 9mo agoImagine finding the highest point on Earth. The bounded space is easy to find. 5E8km^2. How many points do you need to find it by brute force searching all of them? It looks like a 10m*10m square is good enough, perhaps 100m*100m is enough. That is 5E12 or 5E10 points. Anyway, you need all of them to detect all the mountains and oceanic trenches. Most of the times, the terrain is quite smooth and you can interpolate like in their example with the Gaussians. Well, except the Colorado Canyon, the Niagara Falls and a long list of sharp features. Also, if you want to detect also buildings, you need like x100 more points. And this is just a 2D problem. When you add dimensions, the problem grows like grid size ^ dimensions and the brute force approach is not feasible. There are a few ideas that are very nice in 1D, but in 100D they are just impossible in a sensible amount of time.