As I’d mentioned, we often apply non-LPE-based environment-solving to constrain the space of heuristics over which we search, as in the tic-tac-toe and math examples. Indeed, it seems that scientific research would be impossible without that.
LPE-based learning does not work in domains where failure is lethal, by definition. However, we have some success navigating them anyway.
I think this is a strawman of LPE. People who point out you need real world experience don’t say that you need 0 theory, but that you have to have some contact with reality, even in deadly domains.
Outside of a handful of domains like computer science and pure mathematics, contact with reality is necessary because the laws of physics dictate that we can only know things up to a limited precision. Moreover, it is the experience of experts in a wide variety of domains that “try the thing out and see what happens” is a ridiculously effective heuristic.
Even in mathematics, the one domain where LPE should in principal be unnecessary, trying things out is one of the main ways that mathematicians gain intuitions for what new results are/aren’t likely to hold.
I also note that your post doesn’t give a single example of a major engineering/technology breakthrough that was done without LPE (in a domain that interacts with physical reality).
It is, in fact, possible to make strong predictions about OOD events like AGI Ruin — if you’ve studied the problem exhaustively enough to infer its structure despite lacking the hands-on experience.
This is literally the one specific thing LPE advocates think you need to learn from experience about, and you’re just asserting it as true?
To summarize:
Domains where “pure thought” is enough:
toy problems
limited/no interaction with the real world
solution/class of solutions known in advance
Domains where LPE is necessary:
too complicated/messy to simulate
depends on precise physical details of the problem
even a poor approximation to solution not knowable in advance
Yeah, it’s clear I wasn’t precise enough in outlining what exactly I meant in the post / describing the edge cases. In particular, I should’ve addressed the ways by which you can gather information about an environment structure in realistic domains where that structure is occluded.
To roughly address that specific point: You don’t actually need to build full-scale rocket prototypes to get enough information about the rocket-design domain to build a rocket right on the first try. You can try low-scale experiments, and experiments that don’t involve “rockets” at all, to figure out the physical laws governing everything rocket-related. You don’t need to build anything even similar to rockets, except in a very abstract sense, to gather all that data.
It’s not done this way in practice because it’s severely cost-ineffective in most cases, but it’s doable. Just an extrapolation of the same principle by which it can occur to us to build a “rocket prototype” at all, instead of all inventions happening because people perturb matter completely at random until hitting on a design that works.
the laws of physics dictate that we can only know things up to a limited precision
In these cases technology is straight-up impossible. If the environment structure is such that only things up to a limited precision work, then there’s no way to build a technology that goes beyond that level of precision, by trial-and-error or otherwise.
This specific limitation is not about whether you need LPE or not; it’s about what kinds of design are possible at all.
I think this is a strawman of LPE
I don’t think it is, I don’t think it’s even a weak man. I concur that there’s a “sliding scale” of “LPE is crucial”, and I should’ve addressed that in the introductory part.
I don’t think my arguments address only the weak version of the argument, however. My impression is that a lot of people have “practical experience” and “the need to know the environment structure” intermixed in their minds, which confuses their intuitions. The extent of the intermixing is what determines the “severity” of their position. I’d attempted to address what seems to me like the root cause: that practical experience is only useful inasmuch as it uncovers the environment structure.
I think this is a strawman of LPE. People who point out you need real world experience don’t say that you need 0 theory, but that you have to have some contact with reality, even in deadly domains.
Outside of a handful of domains like computer science and pure mathematics, contact with reality is necessary because the laws of physics dictate that we can only know things up to a limited precision. Moreover, it is the experience of experts in a wide variety of domains that “try the thing out and see what happens” is a ridiculously effective heuristic.
Even in mathematics, the one domain where LPE should in principal be unnecessary, trying things out is one of the main ways that mathematicians gain intuitions for what new results are/aren’t likely to hold.
I also note that your post doesn’t give a single example of a major engineering/technology breakthrough that was done without LPE (in a domain that interacts with physical reality).
This is literally the one specific thing LPE advocates think you need to learn from experience about, and you’re just asserting it as true?
To summarize:
Domains where “pure thought” is enough:
toy problems
limited/no interaction with the real world
solution/class of solutions known in advance
Domains where LPE is necessary:
too complicated/messy to simulate
depends on precise physical details of the problem
even a poor approximation to solution not knowable in advance
Yeah, it’s clear I wasn’t precise enough in outlining what exactly I meant in the post / describing the edge cases. In particular, I should’ve addressed the ways by which you can gather information about an environment structure in realistic domains where that structure is occluded.
To roughly address that specific point: You don’t actually need to build full-scale rocket prototypes to get enough information about the rocket-design domain to build a rocket right on the first try. You can try low-scale experiments, and experiments that don’t involve “rockets” at all, to figure out the physical laws governing everything rocket-related. You don’t need to build anything even similar to rockets, except in a very abstract sense, to gather all that data.
It’s not done this way in practice because it’s severely cost-ineffective in most cases, but it’s doable. Just an extrapolation of the same principle by which it can occur to us to build a “rocket prototype” at all, instead of all inventions happening because people perturb matter completely at random until hitting on a design that works.
In these cases technology is straight-up impossible. If the environment structure is such that only things up to a limited precision work, then there’s no way to build a technology that goes beyond that level of precision, by trial-and-error or otherwise.
This specific limitation is not about whether you need LPE or not; it’s about what kinds of design are possible at all.
I don’t think it is, I don’t think it’s even a weak man. I concur that there’s a “sliding scale” of “LPE is crucial”, and I should’ve addressed that in the introductory part.
I don’t think my arguments address only the weak version of the argument, however. My impression is that a lot of people have “practical experience” and “the need to know the environment structure” intermixed in their minds, which confuses their intuitions. The extent of the intermixing is what determines the “severity” of their position. I’d attempted to address what seems to me like the root cause: that practical experience is only useful inasmuch as it uncovers the environment structure.