Reading the last few (longer) posts on yours, it seems you have a keen interest in emergent behavior among very simple agents. It reflects your interest in game theory and/or swarm intelligence. I am poignantly reminded of the lectures I took from the great Georg Kampis (
https://kampis.web.elte.hu/) on the simulation of complex systems through simple agents. There were many interesting discussions throughout, some that stood out were, how building a highway through a natural habitat (like a forest or a desert) whereby the animals of the same species or prey/predator are separated can cause extreme changes in the diversity of the population. Another one was floods and their causes and a recurring pattern that is observed in their devastation style.
Yes building blocks and simple agents interest me greatly. These are connected to the eigenvalue problem intrinsically....be they linear or non-linear....i.e they either represent something of the eigenvector directly or characteristic in close conjunction/derivative of it.
The sensitivities (which you mention with animals in this case w.r.t their habitat and some new forces introduced) of the larger space and its vector field of interest to them...and of course the bounds of relevance past which things break down gradually or abruptly (as your first post regd the Indian mathematician lady's discovery some pages ago).
Eigen itself means "own" or "characteristic" in German.
One sees it manifest in lot of structured puzzles for example that are more tangible for people to behold and grapple with patterns and make some early understanding on the matter at hand even if they are unable to solve it.
Take the rubiks cube and solving it by "brute force" layer by layer.
The first layer is pretty nominal (I can teach this to most people in under 10 minutes with them able to replicate it)....these are where the first simple agents process (basic rules of getting something moved and fixed relative to something else, cross and corners as I call it) illustrate themselves.
The second layer is the first real algorithm (since you have to not upset the first layer, so you need a longer cohesive extension of the earlier simple agents)... I call it the T algorithm, and this one takes more time for folks to learn/implement compared to 1st....it is not so nominal (to place basically up to 4 edge squares).
Then the third final layer involves advanced algorithms (the easiness "breaks down" substantially and exponentially as it would further do so if you move to a 4v4 rubik and its 4th layer). Replicating the cross this time is harder than with 1st layer...and the corners as well).
Then finding even better algorithms and intuition "on the fly" where you need not do it layer by layer for more optimal solving is its own longer heading to get into....I have only had so much time to get into these....since to me I have a solution that works in reasonable time already.
I'm a chess player (elo around 2100) as well, and you see same pattern in it being common accepted knowledge for "normie" skill levels to simply know 1. e4, d4, c4, Nf3 as the best by test 1st moves for white and then the responses by black for them to make some opening repertoire (ruy lopez, QGA/QGD, french, italian, pirc, slav, indian et al.. and all their further variants....you name it).
But the actual complexity of the game increases exponentially further away from starting move (and its set of best simple agents from feedback of millions of games) given possibility tree expansion even though the core simple agents are consistent always (i.e the ways pieces move and other rules)....so it all boils down to the logic and intuition being as close to the eigenvalue problem so to speak to keep this inflation/drift (to suboptimal cascade and error proliferation etc) as mitigated as possible.
But this is the pattern of increasing complexity that transcends and connects to why the mapping broke down at some dimensional level as illustrated in that mathematical discovery you mentioned.
I jotted down back then (depending on how the convo would turn out here) in my notebook one representative investigation (there are many that could be done) with basic building block phenomenon in the early counting numbers compared to later ones.
In that if you express all numbers as: dots and jumps connecting dots (i.e the initial simple agents or topological units as I will call them for this purpose....not fully accurate, but it will do) and can each successive induction be defined completely using all before it.
1 would be just one dot: o (topological precursor, lacks a jump)
2 would be 2 dots with a jump in between: o - o (basic topological unit)
3 would similarly be: o - o - o (or topologically 2 + 2)
4 would be o - o - o - o (or topologically 3 + 2)
Up to 4, you can always define by using everything that has come before it entirely..
But with 5: o - o - o - o - o , this can no longer be done
it can topologically said to be 3+3 or 4+2, but there is no way to use 2, 3 and 4 completely in one definition with rules we have set in this investigation.
There is a more complicated "through the looking glass" side investigation where you go in opposite direction and have negative jumps where it can be shown you can define 5 from what 6 is (and define 6 from what 7 is and so on) using the same basis of units....which I won't go into as its going to get difficult to illustrate properly....but basically there exists a breakdown between 4 and 5 as to directional preservation in this induction "populating" process.
This is why I brought up Galois before, the root of the issue he discovered when it comes to polynomial factorisation is very much related to the building blocks and voids that can no longer match at some point with "twists, turns" applied in a growing dancing chairs game so to speak (as to elegantly proving why the quintic has no algebraic solutions unlike the quartics, cubics and quadratics and nominal 1st orders).
i.e What does not neatly align like before by the very proliferation of numbers and permutations/transformations and 1:1 and onto mappings based upon them (and what this means for when they represent whole dimensions and their mappings rather than just countable units) from early simple start (1, 2, 3 and sometimes a few more) to much larger inductive finer resolutions so to speak on march to infinity.
This is the simplest way I can explain that (why things break down and get exponentially complicated, it has to do with the numbers themselves doing so relatively quickly after they "get started")....and connect it (for now) to how this discussion all started. Hope it wasn't too confusing heh.
When you have non-living units, you can model and map these fairly robustly the more (combined intellectual lifetimes you have at hand to grapple with it) you throw at it.
When its living units (i.e say human lives), you have same process at hand, but more X-factors as humans are not so predictable like say air molecules to integrate stochastically with brownian motion et al (given consistent forces and spherical volumes of interaction etc) to develop thermodynamics and/or navier stokes....and why these are reliant on very large population numbers + cohesive characteristics from that.... and dont apply so well to small or tiny populations where randomisation starts to break in as a factor again (sort of the inverse to the earlier small number vs large number phenomenon).
But some things do normalise more with larger collective populations that can be studied w.r.t authorities that are much more finite (i.e say 200 countries with 8 billion people in total.....8 billion is a far larger number than 200)....making the calls for them. That is how game theory fits into my reference w.r.t say physics which I am much more comfy with....given my own time integrals invested etc. But what you dont know as much about (but you sense similarity or utilitarian use in some way) is often more interesting to delve into with later spare time.