Re: simulation as a causal/inferential "chimera"

[Tim Gwinn <***>]

Steve,

>
> Tim,
>
> Good point. I did not see that quite this way. And I
> think this is indeed different from Hertz's
> definition.


TG: I am not sure it differs from Hertz's. I think it is just less
explicitly stated than in Rosen's formulation.

>
> I agree with you on this. Still, suppose we
> successfully established a congruence between the
> relationships among the observables of a plane and the
> relationships among images in a software simulation.
> We 're successfully encoding/decoding thus the MR
> commutes. Clearly, this is possible - it's done all
> the time in engineering.


TG: Good question. I hope I have a good answer. :) This is where we have to
be careful. Essentially, we can't directly establish a congruence of
entailments between the object system and the simulation. This is because in
the simulation, all the entailments are material cause (i.e., all inputs to
the hardware), and so in mapping from the object system to the simulation,
we are mapping both material and efficient causes of the object system to
entirely material causes in the simulation. As Rosen says about this,
"Nothing could more starkly illustrate the anomolous characer of simulation
and the mischief that can arise through its confusion of causal
categories."[LI 234]

If we are very careful in writing our programs, and keep track of these
mappings, then we can avoid any "mischief" and we can map back to the object
system, unraveling the collapsed causal structure back to its original
character. Often, though, once something is coded into a simulation, and it
is indistinct as to causal categories, we can easily lose our ability to map
back. The phrase "its all just software" can fool us into rewriting code in
ways that destroy the original mappings. Also, in simulations the concern is
often with the output values, so once the encoding of entailments is done,
the focus is on the output values, and the correctness of the output values
can appear as if they are a proxy for the correctness of the mappings back.
But values are only one aspect of decoding, the other is the entailments.
Hence, one concern with "mischief".

Along these same lines, it is not only the distinct categories of the causal
structure that is an issue, but the type of causal structure involved.
Specifically, causal loops cannot map into predicative steps. Instead, we
use algorithms which numerically (or otherwise) approximate the behavior
resulting from those loops. But such algorithms, useful as they are, cannot
map back to the causal loops in the object system.  So there is no
congruence of entailments in such a case.

The notion of 'simulable model' (or 'computable model') avoids the
"mischief" because it mandates that the predicative entailment of the
hardware (i.e., at the read head of the Turing machine it realizes) must be
congruent with some entailment in the object system. Therefore, the causal
categories remain distinct rather than being coalesced into material cause
as all software.

Regards,
Tim