simulation vs. mimesis

[Steve Johnson <***>]

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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