> -----Original Message-----
> From: Nanograte Knowledge Technologies via AGI [mailto:[email protected]]
> 
> If I understood the first part of your thought correctly; agents could be
> collaborative-type of quanta forming some kind of generative frequency,
> relative to the properties of the agent form?
> 

Well, yes having many similar agents communicating and coordinating via DNA
quantum communication mimic in design and software. I know it's not
determined yet how this works biologically but it doesn't have to be there
is enough evidence and knowledge to work it that way and perhaps there are
indications it will produce results - this model is a form of combined
analog and discrete computation. Analog frequencies from discrete agents
generating hybrid patterns...perhaps patterns of adaptive entropy within its
operational complexity. 

> On the second part; each agent should be a hard-coded fractal, with the
> scalability property being a replicated constant?

Uhm - possible. I'm thinking agents would have complexity somewhere between
that of a cellular automata and a simple unicellular organism, towards the
lower end of course. Core defined by sets of mathematical tuples initially
for example a finite state machine automata tuple, but having advanced
dynamics of communication complexity, peer to peer, group and cluster
forming capabilities...Could they be fractal based and maybe fractal based
CA? I don't know. Tuples allow a vast spectra of higher order interlocking
automata categories. But perhaps fractal based should be explored for the
potential of recursive self-improvement. 

> Some type of soft-coded, management system gets all the pieces working in
> the purposed direction?

The structure needn't closely mimic biology, for example every agent needn't
carry around it's DNA there can be a community copy. Agents might only carry
changes for resource optimization. Oher biological pieces can be thrown out
as not needed in software world like cell walls. And importantly a cell
needn't be a "cell"... 

> Last, I noticed your point on "feedback".
> If open-looped (probably recursive), closed-looped (probably self
recursive).
> To be learning, one would probably require both?

The structure of individual agents should be flexible enough so that it
communicates and incorporates systemic behavior. That would include feedback
mechanisms. A main idea would be that it's self-organizing ability need not
be biologically restricted but restricted along the lines of contemporary
computer based technology. But like you say the system, aside from
individual agents can be recursive that's interesting.

BTW I'm just throwing around some ideas here on a complex adaptive MAS that
has numerous similar agents. I'm sure there are many systems that could be
built differently with just a few agents having highly specific functions or
one agent with many different internal functions. I do suspect the many
similar agent model could have more adaptive utility but I could be wrong I
just don't know.

John







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