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He (Robert Rosen) also said that anything can be a model if it
accurately correlates to aspects in the real system it models. He also said that
a system can be a model of another system-- when we use it that way. The answer
to the question; "What is a model?" will depend on context. When is a simulation
not a model? When you want to understand underlying entailment of the natural
system you are purporting to model. When is a simulation also a model? When you
are modeling observables. Therefore, the definition of "model" is a
definition that is entirely context dependent for each instance of use. You
can't argue it in generalities when it comes to a concept like this one. That's
what this confusion is being driven by: There are times when a simulation is a
model... times when it isn't, ...and times when it is a very poor model (in
other words, it is intended to be used as a model but it shouldn't be used
as a model because what you need the model to do is not encoded into the
model-- it does not commute in the necessary way with the natural system).
This third case is what Tim is talking about.
You can model more than the entailment of system organization. My
father wrote extensively about modeling relations and the reason is because it's
a complicated subject and to model something well requires many aspects of human
judgment and discernment. It's partly an artform, in that intuition and talent
play crucial roles in the process. You have to know what you need the model to
do before you begin and trouble can start even with those decisions. This
is the case with using simulation to try and learn about underlying entailment
relations.
Judith
----- Original Message -----
Sent: Friday, December 31, 2004 1:21
AM
Subject: [ROSEN] simulation vs.
mimesis
Judith,
It seems that there is a confusion between the
notion
of simulation and mimetic research strategy. From my
reading of
Rosen he used the term "simulation" in the
precise sense that Tim
describes, that is, in the
computer science sense of this term (software
vs.
hardware). The entailment structure of the simulation
is that of the
hardware and thus it is not generally
in congruence with that of the
natural system.
Rosen separately criticizes the mimentic
research
strategy which seems to be what you mean by
simulation. He
says: "... I shall concentrate on one
ancient strategy of mimesis. The idea
is that a
material system manifesting "enough" properties of
organism
*is* an organism; a system manifesting
"enough" properties of mind has a
*mind*." He then
goes on to criticize this as a research
strategy
because it merely replicates observables but ignores
the causal
bases. His argument is that if you ignore
the causal bases you cannot learn
anything about the
sytem being modelled from your mimic even if the
two
systems are commuting for a period of time.
As I understand in
Rosen's usage mimesis and
simulation are different terms even though in
normal
usages these words are synonyms.
- Steve
---
Judith Rosen <***>
wrote:
> Tim,
>
> Define "simulation".
>
>
To simulate something is to... what?
>
> In the example you cite,
there is no argument over
> the fact that
> simulation is not a
congruence between entailment
> structures. However,
> there is
congruence over external observables. So...
> in the case where
>
you are modeling a storm for some film you're
> directing (setting: "...
> it was a dark and stormy night..."), the external
> observables
are
> those properties you need to model. In the case
> where you
are trying
> to predict what the weather in some location is
>
going to be like on
> next Thursday... you must model different
aspects
> which correspond to
> entailment structures. My
father's point is that
> human beings tend to
> think if they can
simulate a system convincingly
> enough, that's the
> same as
creating an exact replica... and human
> beings also tend to
>
think that, because we can fool ourselves and each
> other with a
> convincing simulation, that systems which "seem"
> complex are
really
> simple underneath.
>
> Judith
>
>
> ----- Original Message -----
> From:
Tim Gwinn
> To: ***
>
Sent: Thursday, December 30, 2004 11:23 PM
> Subject: Re:
[ROSEN] simulation vs. model
>
>
>
Judith,
>
> I disagree entirely that simulations are
also
> models, in the sense
> in which your father used those
terms. He explicitly
> distinguishes
> between modeling and
simulations in LI ch. 7. On p.
> 200, for example:
> "Simulation
is thus not a congruence between
> inferential entailments."
> A
simulation is not a modelling relation -- it fails
> the requirement
> that the encoding/decoding bring the two entailment
>
structures into
> congruence.
>
>
Regards,
> Tim
>
>
> -----Original
Message-----
> From: ROSEN Forum
>
[mailto:*** Behalf Of
> Judith
Rosen
> Sent: Thursday, December 30, 2004 10:50
PM
> To: ***
>
Subject: Re: simulation vs. model
>
>
> I've said it before but it bears repeating:
All
> simulations are
> also models. My father said many times
that any
> system can be
> "simulated". That means there are
aspects of any
> given complex system
> which can be reproduced
with high "commutativity"
> with the original
> system. What he
was pointing out was that just
> because some model gets
>
external, observable aspects of the system right
> doesn't mean it gets
> all aspects right. In other words, don't forget that
> the
simulation is
> only a model of the system, not a reproduction of
an
> identical system.
>
> Any
"random" set we generate becomes a repeating
> pattern if you
>
close the loop. Randomness is a local, finite
> property and is in
the
> eye of the beholder.
>
>
Judith
>
>
>
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