I'm not clear on where/why one draws the line between artificial and natural.   
Artificial things have resulted from natural processes.  These higher-order and 
relatively sharp fitness landscapes have mesas we call features.   They usually 
don't involve people dying or failing to reproduce, but they do involve 
organized behavior by humans stopping, e.g. companies that go bankrupt.    A 
continuous integration system running regression tests seems to have some 
properties of selection.

-----Original Message-----
From: Friam <[email protected]> On Behalf Of ? glen
Sent: Monday, November 29, 2021 6:14 AM
To: The Friday Morning Applied Complexity Coffee Group <[email protected]>
Subject: Re: [FRIAM] The epiphenomenality relation

Right. Agnostic discovery of the artifacts resulting from an artificial machine 
comes much closer to what happens in natural systems, yes. Those artifacts 
would only be considered secondary or side-effects IF the exploration were NOT 
agnostic, motivated. You can only separate the artifacts into primary vs 
secondary IF you had a purpose in the assembly. No purpose, no distinction of 
primary vs secondary.

But what you can do is measure the impact of all the resulting artifacts, on 
some scale, and order them that way, a distribution of primacy. Outcome O1 
might be Y times more impactful, downstream than outcome O2. If THAT were what 
we meant by "secondary" effect, then it would be less laden with intention.

But that's not what Nick seems to be doing. By insisting that some effects are, 
by definition, secondary and others primary, he's asserting an 
intention/purpose to the assembly. 


On November 28, 2021 9:40:42 PM PST, Marcus Daniels <[email protected]> 
wrote:
>An ab initio simulation of a biochemical system would have a foundation of 
>some human-engineered code and the atomic model simulated might have some 
>simplifying assumptions.    The low energy configurations and dynamics are 
>discovered, not engineered.  Yet it is all reproducible on a digital computer 
>with precise causality and in some cases has shown fidelity with physical 
>experiments.
>
>> On Nov 28, 2021, at 9:14 PM, ⛧ glen <[email protected]> wrote:
>> 
>> This sounds like impredicativity, which can be a problem in parallel 
>> computation (resulting in deadlock or race). Unimplemented math has no 
>> problem with it, though. And I'm guessing that some of the higher order 
>> proof assistants find ways around it. A definitional loop seems distinct 
>> from iteration. So, no; I don't see a problem with iteration in digital 
>> computation. I simply don't think the intelligent design we do when 
>> programming is analogous to biological evolution. The former clearly has 
>> side effects (epiphenomena). I argue the latter does not.
>> 
>>> On November 28, 2021 5:40:31 PM PST, Marcus Daniels <[email protected]> 
>>> wrote:
>>> Glen had said something a while ago implying that (that trivial meaning 
>>> for) loops were somehow more challenging for digital computers.    I didn’t 
>>> get it.
>>> 
-- 
glen ⛧


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