You’re saying a Solomonoff Inductor would be outperformed by a variant that weighted quick programs more favorably, I think. (At the very least, it makes approximations computable.)
Whether or not penalizing for space/time cost increases the related complexity metric of the standard model is an interesting question, and there’s a good chance it’s a large penalty since simulating QM seems to require exponential time, but for starters I’m fine with just an estimate of the Kolmogorov Complexity.
Well, I’m saying the possibility is worth considering. I’m hardly going to claim certainty in this area.
As for QM...
The metric I think makes sense is, roughly, observer-moments divided by CPU time. Simulating QM takes exponential time, yes, but there’s an equivalent exponential increase in the number of observer-moments. So QM shouldn’t have a penalty vs. classical.
On the flip side this type of prior would heavily favor low-fidelity simulations, but I don’t know if that’s any kind of strike against it.
You’re saying a Solomonoff Inductor would be outperformed by a variant that weighted quick programs more favorably, I think. (At the very least, it makes approximations computable.)
Whether or not penalizing for space/time cost increases the related complexity metric of the standard model is an interesting question, and there’s a good chance it’s a large penalty since simulating QM seems to require exponential time, but for starters I’m fine with just an estimate of the Kolmogorov Complexity.
Well, I’m saying the possibility is worth considering. I’m hardly going to claim certainty in this area.
As for QM...
The metric I think makes sense is, roughly, observer-moments divided by CPU time. Simulating QM takes exponential time, yes, but there’s an equivalent exponential increase in the number of observer-moments. So QM shouldn’t have a penalty vs. classical.
On the flip side this type of prior would heavily favor low-fidelity simulations, but I don’t know if that’s any kind of strike against it.