An agent can only flip so many bits per second. If it gets stuck in a
computational conundrum it will waste energy that should be used for
survival purposes and the likelihood for agent death increases. 


Avoidance behavior for impossible computation is enforced.


Mathematics is a type of database for computational energy storage. All of
us multi-agent intelligences, mainly mathematicians, contribute to it over


How long did it take to invent the wheel, but once the pattern is known, it
takes just a few bits to store.


That's one obvious method of the leveraging, but this could be, and is, used
all over the place. 




From: Jim Bromer [] 


How would a mathematical system that is able to leverage for unnecessary or
impossible computation work exactly.  What do you mean by this?  And how
would this work to produce better integration of concepts and better
interpretation of concepts? 


On Fri, Aug 13, 2010 at 4:25 PM, John G. Rose <>

> -----Original Message-----
> From: Jim Bromer []

> On Thu, Aug 12, 2010 at 12:40 AM, John G. Rose <>
> wrote:
> The ideological would still need be expressed mathematically.
> I don't understand this.  Computers can represent related data objects
that may
> be best considered without using mathematical terms (or with only
> mathematical functions related to things like the numbers of objects.)

The difference between data and code, or math and data, sometimes need not
be as dichotomous.

> I said: > I think the more important question is how does a
general concept
> be interpreted across a range of different kinds of ideas.  Actually this
is not so
> difficult, but what I am getting at is how are sophisticated
> conceptual  interrelations integrated and resolved?
> John said: Depends on the structure. We would want to build it such that
> happens at various levels or the various multidimensional densities. But
at the
> same time complex state is preserved until proven benefits show
> Your use of the term 'densities' suggests that you are thinking about the
kinds of
> statistical relations that have been talked about a number of times in
> group.   The whole problem I have with statistical models is that they
> typically represent the modelling variations that could be and would need
to be
> encoded into the ideas that are being represented.  For example a Bayesian
> Network does imply that a resulting evaluation would subsequently be
> into the network evaluation process, but only in a limited manner.  It
doesn't for
> example show how an idea could change the model, even though that would be
> easy to imagine.
> Jim Bromer

I also have some issues with heavily based statistical models. When I was
referring to densities I was really meaning an interconnectional
multidimensionality in the multigraph/hypergraph intelligence network, IOW a
partly combinatorial edge of chaos. There is a combination of state and
computational potential energy that an incoming idea, represented as a
data/math combo, would result in various partly self-organizational (SOM)
changes depending on how the key - the idea - effects computational energy
potential. And this is balanced against K-complexity related local extrema.

For the statistical mechanisms I would use for more of the narrow AI stuff
that is needed and also for situations that you can't come up with something
more concrete/discrete.


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