Re: Anticipatory Systems

[Jerry Zhu <***>]

Judith,

Both feedforward and feedback control are common in
machine based control system. They are routined taught
in undergraduate texts.  

Anticipatory systems can be simple systems being
algorithmic based such as electrical or mechanical
systems.

Biological systems (1st and 2nd order autopoiesis) are
anticipatory and model-based.  They are subcategory of
living systems.  Social systems (3rd and 4th order)
are different kind model-based anticipatory systems.

Model based ASs have inductive capacity that
characterise learning systems.  The implication is
that computers are not learning machines.

Jerry

--- Judith Rosen <***> wrote:

> Hi Jerry,
> 
> One of the applications for studying natural
> anticipatory systems is 
> to develop the ability to create anticipatory
> controls for our own 
> technological needs. He used a high-tech camera as
> an example of a 
> machine with anticipation built in. He recommended
> that our modes of 
> government and city planning, social system
> analysis, etc, all be 
> examined for ways to build in a "feed-forward"
> control system rather 
> than purely feed-back. It's important to note that
> while all living 
> systems are anticipatory they also have the
> capability for purely 
> reactive behavior as well. That's something all
> systems possess. But 
> anticipatory controls are superior under most
> circumstances because 
> they prevent the system from entering an "error
> state". An ounce of 
> prevention is worth a pound of cure!
> 
> I would dispute that these encoded models are all in
> the genes, Jerry. 
> There's so much more that's going on than just
> genetics.
> 
> Judith
> 
> 
>   ----- Original Message ----- 
>   From: Jerry Zhu
>   To: ***
>   Sent: Thursday, February 03, 2005 9:54 AM
>   Subject: [ROSEN] Anticipatory Systems
> 
> 
>   --- Judith Rosen <***>
> wrote:
> 
>   How the information in these internal predictive
>   models is encoded, how it is integrated with
> "real"
>   behavior of self/environment, how it acts on
> system
>   behavior... these are all wide open areas which
> are
>   just screaming for one of you guys to pursue.
> 
>   Judith,
> 
>   A robot is also qaulified as being anticipatory.
> It is
>   quit common practice to have machine learning,
> pattern
>   recognition to learn environment and anticipate
>   consequances of future actions so to adjust
> current
>   action. A robot can learn environment and get
> around
>   obstacles along the way.  These type of ASs are
>   algorithmic such as computers and they are closed
> in
>   the sense that the change of environment is
>   predetermined.  The description of self and
>   environment is syntactic. Its mechanism is
> deduction.
> 
>   Life as being anticipatory is model-based intead
> of
>   algorithms based.  A insect changes its behavior
> to
>   adapt to evironmental change not thro genotype but
>   thro mutation of the genes.  New genes are created
> in
>   next generation that are hypothesis not in older
>   generations.  New behaviors are generated by
>   interpretate the new genes.  This process is
> inductive
>   and semantic.  New knowledge is created by
> enlarging
>   the understanding of environment and self thro
> these
>   new genes or hypothesis.
> 
>   Jerry
> 
> 
> 
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