Re: Societal collapse

Posted by Steve Smith on
URL: http://friam.383.s1.nabble.com/Societal-collapse-tp7597392p7597394.html

J -

Is it possible to create agent-based models of societal collapse? This Nature article argues human societies have mind- boggling complexity, but I am not so sure if it is impossible.

I appreciate the link to the Nature article... I particularly liked the caution about misuse of the "Retrospectoscope" , and the reference to Hari Seldon and PsychoHistory.   "... societal spasms are cyclic" seems nearly tautological, but a good reminder.    I appreciate that many are now treating global socio-economic-political systems (coupled with the earth-systems) as a truly complex system as best they can.

Of course it is possible to build an ABM in this domain...  bit as the article gestures toward, there is no bottom to the possible complexity (at least down to Glen's previous reminders to us that our individual microbiome is a key part of our "selves" in more ways than simply accounting for body mass or cell count).

Unfortunately we aren't just dealing with the risk of our multiple (highly coupled, but nevertheless diverse) facets of societies and whole societies collapsing and taking one another down like dominoes (or a house of cards),  but the earth-systems our high-tech, energy-and-minerals-and-plant-products-hungry  society depends on being able to draw from (exploit?).  

We looked at an SEIR/ABM covid-model for NM at the individual level which seemed (barely) tractable on a single machine (memory size)...    I have worked with Systems Dynamics models which are highly aggregative and we even ran 100,000 samples from the World3 model from 1900-2100 as a test/demonstration last year.   The World3 model focuses on Economics and Resource Utilization and was conceived around the idea of "Limits to Growth"...  it doesn't really do justice to more subtle societal issues (like social justice, massive political shifts, personal violence, etc.)   Within the 10^5 parameter sweep we started with there are (naturally) large subregions where human life becomes acutely miserable.   There are lots of criticisms of the model and it IS very long of tooth.

  I'd be interested if anyone knows of ABMs or Discrete Event Simulations that aspire to study more than the smallest of subsets. 

Our experiments with World3 were as much about studying high dimensional ensemble-problem sets where intuition can be used to double-check the results, as it was about the problem domain of impending collapse.

This 2D projection of a 3D "projection" based on an 11D Self Organizing Map (SOM) was our "best shot" at analyzing this 100k ensemble.   Without stereography or motion parallax, the 3D structure is probably hard to see... it *may* be evident that one of the most notable features is "continuity" that this appears to be a complex 2D surface "folded" into 3D.   The 2D continuity is at least partly a direct artifact of our choice of SOM focused on preserving local distances.   The coloring is on a red-blue spectrum with human population encoding population (ending population 2100).  One of the surprising artifacts found in this rendering is the relatively regular distribution of high/low population peppered through the otherwise dominantly low/high regions.   An obvious "positive" correlation between "good results" and "populations" shows that the sooner we have a population collapse, the better the chance that the remaining population will enjoy a high quality of life (by some measure).    We have many hypotheses to test on this rendering, such as whether the "1D edges" of the embedded surface represent interesting (and relevant to the problem not our choice of encoding) samples.   One partial result is that (within our sampling) these extrema don't have any of the "contrary" samples (high among low or vice-versa)....

This work is temporarily on hold, but the same methods are being explored on other problem sets (where there is funding)... 

The main point of this example is that complex models yield highly complex results and it is not always obvious or easy to decide what the truly interesting "trade space" is, and whether or not there are interesting parts of these high-dimensional landscapes that allow for some  useful intuition. 

- Steve

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