[MUD-Dev] Virtual machine design

[Ola Fosheim Grøstad <olag@ifi.uio.no>]

Chris Gray wrote:
> of. Go examine the world of supercomputing and parallel processing (my
> day job is more in that area) - as new power becomes available, new types
> of more accurate simulations become possible, and they are more valuable
> than the less accurate ones. The chemists, physicists, biologists, etc.
> who use the massive computer power always need more for the next step
> in their work. It is this kind of demand increase that I'm talking about.

Well, ok, maybe, not sure if one should believe people using Fortran, but
hey I could be wrong :-) (I'm not going to rule out laziness or prestige,
but that's OT)

Anyway, that does not apply to MUDs. In research on the "laws of nature" you
want as much accuracy as you can get. It can even be fatal if you are off by
some small factor and you have something fixed to compare your results to! 
A MUD is in nature much more like Computer Graphics. You don't care about
whether it is real or not, you only care about how it is perceived. Some go
for "photorealism" (which computationally can be quite unreal), others for
"believable", yet others go for "interesting".  Basically, you cheat as much
as you can get away with, you sacrifice efficiency for flexibility only in
areas where you need to be flexible. 

If it looks right, then it is right!

This is art, not science 8-)

> Noted. Note also, however that discrete event simulation is one of the
> most compute intensive areas around, and it is used a lot, in order to
> simulate complex systems where no general rules for overall behaviour
> are known. Often, the system is such that it is believed that no overall
> rules *can* exist, because of the chaotic nature of the system.

Hmm.. In a MUD I would vote for laziness and development costs, because WE
invent the rules!  The main advantage of a fullblown simulation over an
optimized model is that it is easy to change and possibly easier to
maintain.  The optimized model takes more brain work, or if you like: a lot
of discrete simulations to arrive at... The real problem is in identifying
strategies which are both efficient, flexible and easy to implement. *sigh*
I'm not saying it is trivial.

Main points: 

o I think we can do a lot better, but the solution might not be obvious.
o Existing explicit simulation approaches may make us blind.
o We DO in fact have a LOT of freedom, because we model a hypothesis
  (about user behaviour) and a fantasy.
o "Nothing" is impossible in a fantasy, but we have to look for the right
  incarnation.

--
Ola Fosheim Groestad,Norway      http://www.stud.ifi.uio.no/~olag/



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