by abelaer on 2/5/25, 2:06 PM with 17 comments
by derbOac on 2/7/25, 3:51 PM
One of the problems in many of these domains is that the potential higher-order interaction space is so large that it's impossible to make inferences about them (in an exploratory way at least). So in genetics for example, there's a lot of genes, and the number of potential combinations of causal factors is huge. Unless you have an a priori reason to think a particular P-way combination of factors is important, it's impossible to search for them because the resources required to make inferences about the P-way interactions exceeds any computational resources available to study them.
This is kind of the idea of emergence, that at some point the information involved in representing a set of higher-order interactions becomes too great to actually represent, so we measure some property of the system that summarizes these interactions instead.
I think the problem scientifically always is knowing whether that information required actually is too large, or whether we just don't understand what is exactly involved. Unknown unknowns or something like that, but where some of the unknowns might in fact be fundamentally unknowable.
I've always found it might be useful to have an estimate of the predictability of some system from some level of analysis of predictors, so we at least know how much we can ever expect to explain from them. In some cases I think this might be doable and others impossible.
by agnishom on 2/7/25, 1:54 AM
by carsonlauer on 2/7/25, 12:03 AM
by cgadski on 2/7/25, 2:57 PM
by a333999 on 2/7/25, 2:23 AM
Here is one:
A is connected to B
B is connected to C
C is connected to A
This is a description in terms of pairs, and from it is trivial to deduce how the rings are connected.
by Onavo on 2/7/25, 4:55 AM