forwarded message from Valdis E. Krebs

From: John Conover <>
Subject: forwarded message from Valdis E. Krebs
Date: Wed, 5 Jun 1996 21:25:31 -0700

Attached is one, of many, recent postings to the Learning Organization
conferences concerning what is now called "informal leaders."
Strangely, the concept is not new. In the late 60's, (when NASA was an
efficient organization-if you can remember back that far,) they were
doing studies into just that. They concluded that the "informal
leaders," (what they called the "inner face," of the organization,)
was was really what made an organization work, not the formal
organizational structure, nor the formal leadership of the
organization, nor the formal decision process of the organization. Out
of these studies came what was to be called "group advice, one man
decisions," which was an organizational paradigm for NASA until the
mid 70's. (It was the methodology used to handle the Apollo 13
crisis-as portrayed in the recent movie-and the likes of Gene Krantz,
the Flight Director during the catastrophe was an ardent supporter.)

The term in the attached, "... concept of 'increasing returns' ..." is
interesting, since it is a term from complexity theory, generally used
in relation to economic issues. (Keynesian, Post-Keynesian, Classical,
and Neo-Classical economics do not recognize it, and, indeed, even
denied its existence. However, starting in the late 1980's, it became
the central paradigm to contemporary economic theory where fractal
analysis and cellular automata-technically called non-linear dynamical
systems theory-are used to model macro-economic phenomena.)
Additionally, it is interesting that the term is used in relation to
organizational "connections" which would tend to indicate that the
"informal leaders" or the "inner face" of the organization could be
modeled using cellular automata, which is, in addition, kind of
interesting since the only reliable analytical technique we have to
model interpersonal and social relationships uses cellular automata
and game-theoretic techniques. See the works of Robert Axelrod and
Stephanie Forrest for details. I think they can be found at the Santa
Fe Institute,, and have proposed using genetic
algorithms in addition to CA/GT techniques to simulate dynamical
outcomes of large systems where game strategies are not constant-ie.,
the game rules have to be developed, or learned, "on the fly."

I think Forrest's C source code is available on that
she used to model a "society" with "massively" many concurrent
players, (or "citizens,") each player playing the game-theoretic
iterated "prisoner's dilemma," (ie., classic multi-player zero-sum
iterated game.) The results of the simulation are astonishing, to say
the least. Most players eventually "discover" and adopt a cooperation
strategy in relation to the "society" as a whole-which is a
counter-intuitive outcome in relation to game-theoretic analysis,
where it can be shown that the only "rational" strategy is
non-cooperative. This was a major issue with John Von Neumann, (who
founded game theory,) and considered it enigmatic that game-theoretic
means predicted that the only rational outcome of humanity was self
destruction. (He made the comment, some time around 1954, that this
was why we are alone in the universe, since the "prisoner's dilemma"
has no solution, all intelligent beings would eventually destroy their



    "John von Neumann and the Origins of Modern Computing," William
    Aspray, MIT Press, Cambridge, Massachusetts, 1990.

    "Prisoner's Dilemma," William Poundstone, Doubleday, New York, New
    York, 1992.

    "Handbook of Genetic Algorithms," Lawrence Davis, Van Nostrand
    Reinhold, New York, New York, 1991.

    "Complexity," M. Mitchell Waldrop, Simon & Schuster, New York, New
    York, 1992.

    "Games and Decisions," R. Duncan Luce and Howard Raiffa, John
    Wiley & Sons, New York, New York, 1957.

And a great www site for the history and introduction of game theory:


John Conover,,

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