WILLIAM FULKERSON (WF28155@deere.com)
30 Dec 1994 12:51:12 GMT

John Conover wrote ....
<Hi Bill. I hate to bug you, but this is kind of interesting. What this
<says is that the best game theoretic strategy is to not be the
<follower. Could you provide any references, preferably to an ftp
<machine. If I remember correctly, the Summer SFI seminars are
<available via ftp, somewhere.

<John Conover, 631 Lamont Ct., Campbell, CA., 95008, USA.
<VOX 408.370.2688, FAX 408.379.9602

John .... Here are the references. If you
want to continue this discussion with
experts, I can put you in contact with Alfred
Hubler himself. Glad to be of help.

Bill Fulkerson

>From Prediction and Adaptation in an
Evolving Chaotic Environment by Alfred
Hubler and David Pines in Cowan, , Pines, and
Meltzer, editors, COMPLEXITY: Metaphores,
Models, and Reality, Addison-Wesley 1994
pages 343-382.

ABSTRACT: We describe work in progress on
computer simulations of adaptive predictive
agents responding in a chaotic environment
and to one another. Our simulations are
designed to quantify adaptation and to
explore coadaptation for a simple calculable
model of a complex adaptive system. We first
consider the ability of a single agent,
exposed to a chaotic environment, to model,
control, and predict the future states of
that environment. We then introduce a second
agent which, in attempting to model and
control both the environment and the first
agent, modifies the extent to which that
agent can identify patterns and exercise
control. The competition between the two
predictive agents can lead to either chaos,
or to metastable emergent behavior , best
described as a leader-follower relationship.
Our results suggest a correlation between
optimal adaptation, optimal complexity, and
emergent behavior, and provide preliminary
support for the concept of optimal
coadaptation near the edge of chaos.

As for ftp sites the only one I have at hand
is the evolutionary computing ECLAIR:
ftp://alife.santafe.edu/pub/USER-AREA/EC/ Evoltionary Ccomputing ECLAIR.

Two URLs of interest are:
http://alife.santafe.edu/alife <Artificial Life>
http://www.santafe.edu/~nelson/swarm <Swarm Simulation>