Exactly Len. And the IFSR book series with Springer is great venue.
George Mobus, PhD.
Associate Professor Emeritus, Institute of Technology
University of Washington Tacoma
Street mail: 1900 Commerce St. Tacoma, WA 98402-3100 Box 358426
Web site: http://faculty.washington.edu/gmobus
Hopefully, in whatever medium we find it, we can avoid the “Pablum” in the pabulum of knowledge. Adequate communication is hard task.
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1) Human beings (more than one)2) Language3) Reasoning through relationships4) Archival representation of artifacts.
Artem Kaznatcheev posted an interesting discussion on his blog under the title “Models as Maps and Maps as Interfaces” that I saw as fitting under this head A reader of Peirce may recognize critical insights of pragmatic thought cropping up toward the end of his analysis, prompting me to add the following comment:
Map and “mirror of nature” metaphors take us a good distance in understanding how creatures represent their worlds to themselves and others. But from a pragmatic semiotic point of view we can see how these metaphors lock us into iconic forms of representation, overstretching dyadic relations, and thus falling short of the full power of triadic symbolic relations that support practical interaction with the world.
Perhaps a different approach that should be investigated is represented here:
Kenneth Lloyd: Perhaps a different approach that should be investigated is represented here:
It looks to me like a walk through that "maze" (a metaphor I'm still using even though only I like it) from the "mainstream" side towards Robert Rosen and Terrence Deacon (but still not Ilya Prigogine (https://en.wikipedia.org/wiki/Ilya_Prigogine#The_End_of_Certainty) and Wolfgang Pauli). See also Daniel Dennett's intentional stance (https://en.wikipedia.org/wiki/Intentional_stance). I mean, where else to look for General Systems Theory? Although many people will probably forever see systems as human constructs, I'll forever be fine with calling consistency and causation in all shapes and forms systems theory.
Information = Comprehension × Extension
Jon:It appears that I was not clear in my original post.Two properties of information are being addressed.The first property is the amount of information (number of transmitted messages or signs.)The second property is the value of information (impact on the message receiver or sign interpreter.)If we consider discrete messages in a noiseless channel, then a quantitative measure of the amount of information in a message may be constructed.However, the value of information in a discrete, noiseless message is dependent on the state and context of the message receiver. The value measure could be different for each message receiver.Take care and have fun,Joe
There are a couple of informational aspects that any system can “tell” us, while at the same time cause us to ask “How does that work?”. These (usually non-equilibrium*) exchanges happen all along a dimension of abstraction --> concretization. I come from a Brussels-Austin (Prigogine) non-equilibrium systems background which can be very different (physical and mathematical) than the purely philosophical approach most in this discussion have adopted. This is not to say that those perspectives cannot converge – they can – but they are very different.
The one area I caution about is in re: the connection of a symbol, like “GST”, to a (one or a small number) of persons identified by their names and philosophies. The problem is that any one perspective – Prigogine, Rosen, Bertalanffy, Popper, Penrose, Aristotle – is incomplete, and each contains errors and omissions (yes, and noise). Yet there is value in each perspective. Can and do these sometimes incongruent perspectives ever converge? It depends, but often yes.
For example, consider the Lorenz Equations (aka Lorenz System of 3 coupled non-linear equations). At some parameters, these do converge at a deterministic result. Others seemingly don’t converge, they vacillate between different attractors (“strange” attractors). Yet, the areas of that attraction are, indeed, identifiable, even if they are never reached (similar to Newton-Raphson or Runge-Kutta). This is a system at (minimally) two levels of abstraction. It is a mathematical system that represents a (actually several) physical systems. More abstractly, it functions as a conceptual system. As we expand or understanding of “system” beyond the “thing” in front of us, the concept of a system emerges by convergence usually at a higher and higher levels of abstraction. It is difficult to “focus in” on any but a small part of that dimension of abstraction.
The concept of a system is an abstraction of patterns we recognize (from the informational patterns “communicated to us” when not at equilibrium) in physical and all “other” systems all along the homological chain from abstract to concrete existence. The problem seems to occur when we conflate “abstraction” with “generalization” (as in General Systems Theory - very different and incomplete perspective). What we need is not a General Systems Theory, but a more correct, more complete Abstract Systems Theory.
*Non-equilibrium of what? Ans. – matter, energy, information or entropy.
For example, consider the Lorenz Equations (aka Lorenz System of 3 coupled non-linear equations). At some parameters, these do converge at a deterministic result.
One might ask, “Is this a system”?
“From a technical standpoint, the Lorenz system is nonlinear, non-periodic, three-dimensional and deterministic. The Lorenz equations have been the subject of hundreds of research articles, and at least one book-length study. “
For example, values of rho < 1, it reaches equilibrium at the origin. There are values that have no periodic behavior.
It is the term used by Lorenz the discoverer of the phenomenon:
Please click on the hyperlinked word “deterministic” in my original post. It will explain what the word means.
See also Sparrow, Colin (1982). The Lorenz Equations: Bifurcations, Chaos, and Strange Attractors. Springer. Referenced by the quote below.
Ken, Duane – To clarify my question: I understand why Lorentz used ‘deterministic’ to characterize his model in general.
But why would a qualifier be used on a special case if it is recognized as applying to all cases? Why was ‘deterministic’ was used to characterize the result of the converging case *in particular*?
It is the term used by Lorenz the discoverer of the phenomenon: