Language, logic and its structure as control systems

Hi, just a share here from the high correlation between what is known as the Paul-Elder model of critical thinking (here what is called the elements of critical thinking) and control theory in general.

The Paul-Elder model of critical thinking identify 8 “elements” which constitute the logic of a subject, those are assumptions, informations, concept, questions, goals, point of view, inference and implications.

These elements appears to define the parts of a control system (here a perceptual control system), so linguistics logical structures appears to be control systems in themselves, which can be transferred symbolically through some to be discovered memetics process.

Here’s the high correlation between the Paul-Elder model and control theory in general as given by ChatGPT-4:
Question: “Analyze the field of control theory using the Paul-Elder model’s element of reasoning.”
Answer: "The Paul-Elder model of critical thinking outlines systematic and methodological processes of reasoning. Analyzing the field of control theory, which studies how to manipulate the parameters affecting the behavior of a system to produce a desired or optimal outcome, using this model can be done as follows:

  1. Purpose: The purpose of control theory is to understand and define the principles and actions that can be manipulated to guide a system to a desired state. This can be applied to various fields from engineering to economics and biology.

  2. Question at Issue: The key problem control theory addresses is, ‘How can characteristics of a system be manipulated to achieve predetermined goals?’ or ‘What needs to be controlled to ensure a system operates as desired?’

  3. Information: This involves the understanding of a system’s structure and function, the factors that can affect its state, and the ways these factors can be manipulated. In engineering, this could involve dynamic systems data, while in biological systems, it might include physiological data.

  4. Interpretation and Inference: Based on the available data, hypotheses are drawn up regarding the control variables. Models and simulations are often created to infer how a system might behave under certain influences.

  5. Concepts: Some of the key concepts of control theory include variables, inputs, states, outputs, feedback, control, stability, disturbance, and optimality.

  6. Assumptions: Control theory assumes that a system’s outcomes can be controlled by manipulating certain variables. It also presumes that the system and its components can be modeled accurately.

  7. Implications and Consequences: The implementation of control theory can lead to the successful operation of various systems, from maintaining the stability of an aircraft, optimizing a production line, controlling the spread of a virus, etc. However, inaccurate models or actions can lead to undesirable results, and in some cases, can be dangerous.

  8. Points of View: Various stakeholders might have different perspectives, such as system designers, end-users, and those affected by the output of the control system.

In short, understanding control theory using the Paul-Elder model requires one to contextualize it, understand its purpose and central questions, gather and interpret relevant information, identify key concepts, understand its assumptions and consider the various points of view related to it."

I think using the Paul-Elder model to model the logic of different topics can be enhanced with other control theory concepts such as variables, inputs, outputs, stability, disturbance, etc, to more precisely model the control system that is behind a concept or a field.

Perhaps, trying to map out these different parts of the Paul-Elder model to the functioning of a toilet or a water clock might better illustrate how they relates to the different important parts of perceptual control systems in general.

This refers to an aspect of engineering control theory. In engineering control theory, the desired or optimal outcome is specified a priori, and the focus of the work is tinkering with parameters until the system reliably produces that outcome. That approach requires a lot of sophisticated mathematics in the loop functions.

In perceptual control theory, an essential part of the work is finding out what perceived variables are under control, and what control system is controlling those as perceptual inputs. Adjusting parameters becomes important for stabilizing and tuning a working model or simulation of a living control system. It is also important for stabilizing and tuning a robotic system designed and built according to principles learned from the investigation of living control systems. A PCT robotic system is not designed to produce outputs desired by the designer; it is designed to control its perceived inputs in accord with internally established preferences for them, just as living control systems do. In PCT, the mathematics is pretty simple, though verbal explanations of the integration of simultaneous equations have been confusing to many people. The heavy lifting is done by essential characteristics of analog computation.

It may indeed be a good system for organizing your study of PCT. That does not amount to a correlation with PCT. I do heartily endorse and encourage learning PCT, whatever study method you use.

I don’t think any field of science has a control system behind it.

Toilet tank, water clock, thermostat, cruise control, these are all systems in which the reference level or setpoint is imposed from outside the system. The person setting the thermostat or the cruise control is a living control system with an internally generated preference for the temperature or the speed of the car.


Phil Runkel is very good at clearing up confusions.

Reconsidering this, scientists practice, maintain, and develop their field over time collectively. (The work of an isolated individual, however brilliant, without corroboration by competent others, is not science. Doing science is inherently and necessarily a social phenomenon.) There is no single control system controlling the collectively controlled variables of the field, but collective control has that appearance (CVs and their reference levels can be identified, observed, and tested with disturbances) until we look for the locations of inputs from the environment and outputs into the environment, and find that they are the senses and effectors of individual scientists.

Here are some links:

Kent McClelland on collective control:

Volume III of Powers of Perceptual Control (Martin Taylor)

As to the idea of fields and concepts having control systems behind, they might be conceived that way in that when the ideas behind those fields and concepts are communicated to say students of the field, the teacher may try to control the student’s perceptions in order to transfer them the knowledge and the student may try to match hiser understanding to the one of the teacher.

Moreover, in fields like in the sciences, the student learn to control hiser perception with feedbacks from his instruments and “reality” (hopefully. So in this way there is like a triple control system between the perceptual control of the teacher, the one of the student, and the one of both to “reality”.
There we may add a fourth control system which would be the logic of science or field in question (which may vary from specific groups to other but still be somewhat enough similar.)

I once read an scientific article on the web about a draft explaining the transfer of memes between people and related it to PCT, it had a rough attempt at describing how control happened as to verify the copying fidelity of the transfer using perceptual reference states. I unfortunately can’t seem to find this paper back.

I think the Paul-Elder model might help in modelling concepts’ memetics transference as well as the transference of bigger knowledge packages. Furthermore, there might be implications for a.i. assisted education or tutoring where the a.i. would insure correct memetics transference of the knowledge of particular concepts or whole parts of fields.

Found back the article, here it is
I guess it could be enhanced using the Paul-Elder model:

Yes, Ted Cloak has been engaged with PCT for many years. Here’s his Researchgate home.

Eetu Pikkarainen has a particular interest in a control-theoretic understanding of how education works (or not).

You’re searching in the right directions, Nicolas, but you name environmental feedback paths that a control system uses which are not themselves control systems (e.g. scientific instruments, or the texts, lectures, tests, and other paraphernalia of education used mutually by teachers and their students for their respective purposes).

We have had many dilettantes flutter through over the years. I very much hope that you are a more serious investigator. The effect can be jarring, depending on preconceptions, as Phil Runkel so brilliantly documented. We all prefer to learn the way a mollusk builds its shell, by accretion to what we have already established. Learning something fundamentally new is a different exposure.