[FRIAM] the arc of socioeconomics, personal and public: was VPN server

glen ☣ gepropella at gmail.com
Wed Apr 19 17:22:11 EDT 2017

On 04/18/2017 06:54 PM, Vladimyr wrote:
> Evolution is operating like a skinflint or miser rarely inventing something totally new. At least since cyanobacteria figured out oxygen usefulness.

Ahh, but whether that's true or false hinges on the inherent ambiguity in the word "new".  So, I posit you are neither right nor wrong.

> The honest resident of the commons is a defective rogue hampered by social morality or gullibility. A lesser creature , a domestic entity. However he does have one advantage , he can learn how to protect himself if he elects to make an effort. Extract simple parameters from to rogue and amplify only those while muting others and you may find they act in a different manner as another species. Yet they both contain the same code managed slightly differently. I recently wrote some code using Growth Factors that produced dramatically different Object appearance and behavior.

Hm.  Before, you stated that a single bimodal agent (one that only behaves honestly when they think they're being observed) could cause chaos in an honest collective.  That implies a fairly straightforward toy model+experiment, wherein we can look for complex maps from simple mechanisms to complicated phenomena.

But now, you're suggesting something much closer to my (conceptual) model of organisms: that we're _all_ hypocrites, we're all both hampered by morality or gullibility _and_ free to commit any crime then lie about it, to varying degrees and over various periods.  In such a model, the most important factors are the _measures_, not necessarily any mechanisms or any putative (objective) phenomena that might be measured.

The collection of measures, is itself complex and multiscale.  Each component (from the tiniest "atom" to the largest sub-collection) has its own set of measures.  E.g. cells, organs, individuals, groups, states, nations, corporations all sense and respond to their environment.  To focus, as you have on the single-scale, measure-dependent concepts like honesty, morality, gullibility, etc. is to over-emphasize one small set of measures to the detriment of all the other measures and their scopes.

Regardless, though, it's from this measure-dominant understanding of the world that I poked Steve about determining the _purpose_ of modeling evolution through politics-space prior to entertaining any models at all.  It's a direct result of a V&V-dominant approach to modeling.  First determine the purpose.  Next determine the measures.  Then, and only then consider the amorphous milieu of possible mechanisms behind the ontological wall.  This results-driven method seemed very strange to the laity prior to the development of test-driven software development.  But it's been a mainstay in engineering for maybe 70 years, now.

> But then they are unlike your creatures.  I use simple functions currently linear and trig since I wish to examine them minutely. By keeping them simple they emulate genetic regulators. 

I don't see my creatures (cells and organs, these days) as very different from what you're describing.  While it's true that I tend to use discrete mappings, they are almost always hybrids (discretized continuous and discrete event) over mixed state spaces (anything from analytical to enumerative types).  Dealing with those mixed state spaces means that complications appear early on, I suspect much earlier than complications that come with what I call "flat" or "thin" models, where all the state spaces _reduce_ to a common, well-defined state space (like ℝ⁴).  Because those complications arise early in the workflow, that means my "creatures" and the models they compose will almost always be simpler than those used in, say, physics-based models.  In fact, it's this over-simplification that allows us to model with these ill-defined creatures and systems at all.

So, my creatures are probably simpler than yours.  And I would posit they are very similar to yours.  Of course, the systems they compose are axiomatic, where, because you can rely on a huge body of well-developed (if not well-founded!) analytical math, it's probable your _methods_, your workflows, are very unlike mine.

☣ glen

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