Exactly Len. And the IFSR book series with Springer is great venue.
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George Mobus, PhD.
Associate Professor Emeritus, Institute of Technology
University of Washington Tacoma
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WRT to Kent Palmer’s and Len Troncale’s work, I see these as some of the many dots in a very large pointillist painting from which a “picture” emerges.
Ken Lloyd
From: syss...@googlegroups.com [mailto:syss...@googlegroups.com] On Behalf Of Aleksandar Malecic
Sent: Wednesday, August 22, 2018 2:21 AM
To: syss...@googlegroups.com
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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Aren't all sciences versions of applied Knowledge Representation Ontology also known as the Sowa Diamond? http://www.jfsowa.com/ontology/toplevel.htmAleksandar
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1) Human beings (more than one)2) Language3) Reasoning through relationships4) Archival representation of artifacts.
Re: Pragmatic Semiotic Information • Discussion 10
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.
Regards,
Jon
Perhaps a different approach that should be investigated is represented here:
http://rsfs.royalsocietypublishing.org/content/8/6/20180041.full
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Kenneth Lloyd: Perhaps a different approach that should be investigated is represented here:
http://rsfs.royalsocietypublishing.org/content/8/6/20180041.full
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.
Aleksandar
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
Aleksandar,
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.
Ken Lloyd
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.[11] “
For example, values of rho < 1, it reaches equilibrium at the origin. There are values that have no periodic behavior.
https://en.wikipedia.org/wiki/Lorenz_system
https://journals.ametsoc.org/doi/pdf/10.1175/1520-0469%281963%29020%3C0130%3ADNF%3E2.0.CO%3B2
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:
<image001.png>
I think deterministic was used by Lorenz as a classifier of the definition of the term “deterministic” for all such 3-coupled, non-linear Lorenz-like systems using the same input perturbation values and the same model parameters, the same behavioral results follow. Compare that behavior, giving the same initial conditions, to systems which do not yield the same behavior given the exact same initial conditions, such as non-deterministic finite automata (NDFA). These are covered and compared with DFAs, almost ad nauseum, in Stephen Wolfram’s “A New Kind of Science”. A specific example might include pseudo-random number generators - such as a Mersenne Twister – given the exact same initial seed value the subsequent resulting patterns cannot be perfectly determined.
WRT encoding data, information, knowledge and meaning, there is a concept of “universal representation” identified by D. Hofstadter based upon A. Turing and K. Gödel. While it has been demonstrated (by Turing and von Neumann) that universal representation is theoretically possible, it is precisely the question of initial conditions that make the conjectures of the resulting behaviors “probably non-deterministic” in practice.
This leads to my conjecture that “there are many more ways to mis-interpret any encoded message than to resolve upon a correct interpretation”. This is probably why Stanley and Lehman identified deception in exploring under-determined problem spaces – the so-called Myth of the Objective.
Ken Lloyd
Len,
Please consider how we go about weather prediction (one of the physical phenomena associated with Lorenz). First, is this attempt at prediction a useful endeavor? Today, we do not consider “one true model” of the weather, but a plethora of models. These provide probable outcomes given alternative perturbations and different contexts (some consider these “assumptions”). One of the things we attempt to realize is the sensitivity of the system to initial conditions to condition our predictions. We refine which potential model is the most likely, plausible and probable. It has been shown that people seem to have a hard time understanding probabilities and their relationships with frequency of occurrence (Yudkowsky, Wasson).
There have been considerable studies regarding expectations and predictions using models – from social science to bio-pharmaceuticals. The underlying problem often relates to the necessity and sufficiency of knowledge encapsulated in the model. All too often, these have been oversimplified by “forgetting” the important parameters – i.e. friction or random variation such as noise.
In systems engineering, it often boils down to determining this necessity and sufficiency of information WRT the system of interest (which is related to risk). One weakness in the current application of SE is relying on too few models (where the SE develops what is believed the “one, true model” of a system). The reality is there are many, and perhaps infinitely many models to consider (which is impossible) so in our search through the under-determined possibility space is incomplete within time and budgetary constraints. In engineering, we tend to apply what we think we know. Sometimes, this is incomplete to a fault, or even wrong. What did you expect (the Sunny Day Paradox)?
Ken Lloyd
Re: “Mersenne Twister – given the exact same initial seed value the subsequent resulting patterns cannot be perfectly determined.” … should be qualified within certain time constraints. Over very long periods, this does resolve into a deterministic pattern.
Len,
I hope everyone realizes that there are important relationships between the (simple?) examples I have provided and the general topic of representation of complex concepts in systems. It extends far beyond the spaghetti images of storm tracks on an electronic weather map. For example, why do we have to use supercomputers and large-scale data acquisition to make and visualize these models? What are the tendrils that relate computation with the necessary and sufficient levels of knowledge – and the epistemology or nature of that knowledge – to the phenomena of interest?
The “whole” of the systems domain stretches human intelligence in “wrapping one’s head around the problems” to almost unimaginable depth and breadth – often beyond what we can perceive, directly. While humans can deal with “a magic number 7 +/- 2 factors”, what happens when the reality presents us with hundreds of thousands of factors, and we find we are uncertain regarding the relative weight and importance of those factors to understanding the problem?
Indeed, a study of Wilson and Crick’s path to discovery of DNA illustrates the messy business of factual discovery we face every day – and we still have very far to go. I recall a panel from Walt Kelly’s “Pogo” (long ago) – “We have met the enemy and he is us.” How can we transcend this? My concern is that the path is not written in the hermeneutics of the past, but presents its own challenges of discovery, today.
Ken
Error: Watson and Crick … not enough coffee this early in the AM.
[A] natural consequence of the belief in “laws of nature” is that there can be no novelty in the future, for future can be calculated from the past. With differential equations, past decides the present (or vice versa) and present decides the future. … This understanding of “causality” should not be confounded with “mundane causality”, where, say, we punish a criminal on the grounds that he is the cause of a crime. “Mechanical causality”, or causality as understood in physics, is incompatible with and excludes mundane causality or human agency. …Newton's laws failed just because of the conceptual confusion arising from the Christian dogmatic belief in eternal laws of nature. … Newton needed the calculus for the formulation of his “laws” (the second “law” needs the derivative with respect to time) and was concerned that the calculus was not “perfect”. (How could the “eternal” laws of God be stated in an imperfect language?) He thought (on his theory of “fluxions”) that calculus (i.e., the time derivative) could be made “perfect” by making time “flow”. (His confusion is obvious, for while things may flow in time, it is meaningless to assert, as he did, that time itself flows.) Anyway, he rejected physical time (as measured by ordinary clocks) as imperfect and chose “mathematical” time (which, he asserted, “flows on without regard to anything external”). That is, to make the calculus “perfect” he made time metaphysical, or known only to God. Alas, physicists too need to know how to measure time in order to do physics! That is, Newton's concern for perfection (of the laws of God) led to his failure to define a physical clock, and that was the cause of the failure of his physics.The Christian theology in mathematics is what has complexified mathematics and made it difficult, as I have explained elsewhere, so eliminating it makes math easy. … As for science, given the massive empirical evidence against the belief in “laws of nature”, it is clear that this Christian dogma ought to be abandoned by science. Physics must be reformulated to allow room for living beings to create a bit of the future. Clearly, also, this requires that we abandon (mechanical) causality.
“The cases of Newton and Stephen Hawking are only examples of how Christian metaphysics has crept into science. In general, this happens because metaphysical assumptions are always present in science, for it is impossible to formulate science entirely in operational terms.Briefly, the common route by which church metaphysics has crept into science is through mathematics, and particularly the mathematics of infinity, related to the church metaphysics of eternity.Newton's problem was with the infinite series of the Indian calculus, as I have explained in detail elsewhere. With regard to the infinite series for π, the naïve European objection was that such infinite series could not be physically summed (since that would take an infinity of time) and summing only some of the terms would result in something imperfect, not eternal truth, hence not mathematics. Note the emphasis on perfection and eternal truth, for Clavius had long ago recognized the practical value of the Indian infinite series (for navigation) and published (in his name) the high-precision trigonometric tables derived in India using infinite series expansions.
Newton needed the calculus for the formulation of his “laws” (the second “law” needs the derivative with respect to time) and was concerned that the calculus was not “perfect”. (How could the “eternal” laws of God be stated in an imperfect language?) He thought (on his theory of “fluxions”) that calculus (i.e., the time derivative) could be made “perfect” by making time “flow”. (His confusion is obvious, for while things may flow in time, it is meaningless to assert, as he did, that time itself flows.) Anyway, he rejected physical time (as measured by ordinary clocks) as imperfect and chose “mathematical” time (which, he asserted, “flows on without regard to anything external”). That is, to make the calculus “perfect” he made time metaphysical, or known only to God. Alas, physicists too need to know how to measure time in order to do physics! That is, Newton's concern for perfection (of the laws of God) led to his failure to define a physical clock, and that was the cause of the failure of his physics.
Similar remarks apply to Stephen Hawking. Singularities are nothing but infinities of some sort arising from a bad understanding of the calculus (and specifically the wrong assumption that the metric tensor must remain twice continuously differentiable, to keep the equations of general relativity meaningful).More generally, the attempts to handle the infinities of the calculus in a “rigorous” way culminated in set theory and the formalist doctrine of Russell and Hilbert (used to axiomatise set theory). Formalism has made mathematics 100% metaphysics. Empirical proofs are deprecated in the manner of Plato, or regarded as contingent truths, compared with logical truths regarded as necessary truths.It is amazing how so many people, who are otherwise intelligent, have swallowed the church line that (its conception of) rationality is universal and so is this metaphysics of eternity (and the resulting mathematics of infinity). If metaphysics were universal, why would we need science?Indeed, the slightest commonsense, or the most superficial acquaintance with other cultures, shows that this Western metaphysics is not universal. For example, all Indian systems of philosophy, without exception, accept the empirical as the first means of proof, while the Lokayata (similar to Epicureans) reject the validity of inference as a means of proof. (This is the exact antithesis of the Western philosophical position that deductive truths are certain, compared to empirical truths.) …”
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Kent,There has been quite a bit of discussion lately on semiotics and how it relates to SS. The thread below already has 75 messages in the chain.I suspect you don't pay attention to the SSWG discussion list. But in this case you might want to take a look and start contributing since it has a direct correlation to all that you are doing.We need to start bringing more of Peirce's ideas into the SS and SE community as I believe this can lead to some major breakthrough. I know that John Sowa has been doing this for a while in the software community but very few SE's are up on Sowa's work.James
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From: Jon Awbrey <jaw...@att.net>
Date: Sun, Jan 13, 2019 at 10:24 AM
Subject: [SysSciWG] Re: Pragmatic Semiotic Information (Ψ)
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