About a million years ago, we developed an agent-based model (except that in
1986 we called them Actor-based models) that did just this.  It was a C^3I
(Command, Control, Communication, and Intel) military simulation in which
battalion-sized organizations would deploy in a rad-war environment.  the
simulation had reconnaissance agents, commander agents, fuelers, and
communications.  It was implemented in KEE (Knowledge Engineering
Environment), a LISP-base AI shell.  The decision logic was implemented in
KEE's rule system. It did not create new rules, but it could disable or
modify existing ones.

The simulation updated it's state, operating on perceived knowledge about
the state of the terrain it was traversing and updating that with "ground
truth" when such became available.  The project was called "The Mobile
Intercontinental Ballistic Missile (MICBM) simulation".  Remnants of it can
still be found by googling:

http://www.osti.gov/bridge/product.biblio.jsp?query_id=0&page=0&osti_id=6940830

If you go here it will cost you $17 to read all about it:

http://www.ntis.gov/search/product.aspx?ABBR=DE87003741

--Doug

-- 
Doug Roberts
[email protected]
[email protected]
505-455-7333 - Office
505-670-8195 - Cell

On Sat, Aug 22, 2009 at 9:13 PM, Russ Abbott <[email protected]> wrote:

> Hi,
>
> I'm interesting in developing a model that uses rule-driven agents. I would
> like the agent rules to be condition-action rules, i.e., similar to the
> sorts of rules one finds in forward chaining blackboard systems. In
> addition, I would like both the agents and the rules themselves to be first
> class objects. In other words, the rules should be able:
>
>    - to refer to agents,
>    - to create and destroy agents,
>    - to create new rules for newly created agents,
>    - to disable rules for existing agents, and
>    - to modify existing rules for existing agents.
>
> Does anyone know of a system like that?
>
> -- Russ
>
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