On Thu, May 25, 2017 at 2:25 PM, Russ Abbott <russ.abb...@gmail.com> wrote:
> A complex system involves agents with the following properties.
>
> - They can accumulate (and store) free energy.
> - They have means to release that energy.
> - They respond to (symbolic) information, i.e., symbols. By that I
> mean that they respond to things on the basis of their internal rules
> rather than as a consequence of physics or chemistry. (In other words they
> are autonomous in the sense that they are governed by internal rules and
> not just pushed around by external forces.) I'm not saying that the
> internal rules are not themselves run by physics and chemistry, only that
> the response of an agent to some information/symbol is minimally if at all
> connected to the physical nature of the symbol. (A bit is a symbol. Bit
> representations don't matter when software looks at bit values. Similarly
> when you see a red traffic light you respond to the symbol
> red-traffic-light, not to the physical effects of the photons -- other than
> to translate those photons into the symbol. Software is a set of rules no
> matter what mechanism executes it.) Of course one of the things agents can
> do is to employ some of its stored energy as part of its response to a
> symbol.
>
> The result of all this is that agents operate in two worlds:
> physics/chemistry and information. A system cannot be considered complex
> unless it includes such agents.
>
I disagree with the your last statement - it is too restricting for the
general field of complex systems.
The criteria you list above are similar to what others have described as
distinguishing properties for the transition from physically
self-organizing systems to living systems. So if you include these
conditions as necessary to be a complex system, of course, you won't be
able to find physical systems that qualify as complex systems.
Example criteria others have used similar to yours:
- onboard free energy stores
- responding to information gradients instead of just force gradients
- responding to kinematic flow fields (1987 Kugler and Turvey) instead
of only kinetic. Eg forces defined on information gradients not just
mass-based.
- Stu's definition of an "Autonomous Agent"
- detect gradients from which it can extract work
- construct system of constraints to extract work
- do work to maintain those constraints
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