Your best guess about the OP's view, or your own view?

Have you come across Loglan? It's been around for a long time, so it will be in the chatbots' training data.

If it is good to lower wild animal populations, what do you think their optimum population would be?

(Epistemic status: not an economist.)

Money is not value, but the absence of value. Where money is, it can be spent, replacing the money by the thing bought. The money moves to where the thing was.

Money is like the empty space in a sliding-block puzzle. You must have the space to be able to slide the blocks around, instead of spotting where you can pull out several at once and put them back in a different arrangement.

Money is the slack in a system of exchange that would otherwise have to operate by face-to-face barter or informal systems of credit. Informal, because as soon as you formalise it, you've reinvented money.

You can't bring a culture back. It would just be cosplay and reenactment. Recording what is is worthwhile only so that later people can learn what was. Who takes the ancient Greek gods seriously today? Who speaks Egyptian? How many crofters are there still? The young vote with their feet and the old die off. "How Ya Gonna Keep 'em Down on the Farm, After They've Seen Paree?"

(I have been busy, hence the delay.)

It sounded previously like you were making the strong claim that this setup can't be applied to a closed control loop at all, even in e.g. the common (approximately universal?) case where we have a delay between the regulator's action and it's being able to measure that action's effect.

I am making that claim. Closed loops have circular causal links between the (time-varying) variables. The SZR diagram that I originally objected to is acyclic, therefore it does not apply to closed loops.

Loop delays are beside the point. Sampling on that time scale is not required and may just degrade performance.

Imagine for sake of argument a apparatus that needs tighter control such that there's actually pressure to optimize beyond the simplest control algorithm.

You are assuming that that tighter control demands the sort of more complicated algorithms that you are imagining, that predict how much heat to inject, based on a model of the whole environment, and so on.

Let's look outward at the real world. All you need for precision temperature control is to replace the bang-bang control with a PID controller and a scheme for automatically tuning the PID parameters, and there you are. There is nothing in the manual for the ThermoClamp device to suggest a scheme of your suggested sort. In particular, like the room thermostat, the only thing it senses is the actual temperature. Nothing else. For this it uses a thermocouple, which is a continuous-time device, not sampled. There is also no sign of any model. I don't know how this particular device tunes its PID parameters (probably a trade secret), but googling for how to auto-tune a PID has not turned up anything suggesting a model, only injecting test signals and adjusting the parameters to optimise observed performance -- observed solely through measuring the controlled variable.

The early automatic pilots were analogue devices operating in continuous time.

Everything is digital these days, but a modern automatic pilot is still sampling the sensors many times a second, and I'm sure that's also true of the digital parts of the ThermoClamp. The time step is well below the characteristic timescales of the system being controlled. It has to be.

People talk about eliminating the cycles by unrolling. I believe this does not work. In causal graphs as generally understood, each of the variables is time-varying. In the unrolled version, each of the nodes represents the value of a single variable at a single point in time, so it's a different sort of thing. Unrolling makes the number of nodes indefinitely large, so how are you going to mathematically talk about it? Only by taking advantage of its repetitive nature, and then you're back to dealing with cyclic causal graphs while pretending you aren't. "Tell me you're using cyclic causal graphs without telling me you're using cyclic causal graphs."

Abductive reasoning results from the abduction of one's reason.

Couldn't resist the quip. To speak more seriously: There is deduction, which from true premises always yields true conclusions. There is Bayesian reasoning, which from probabilities derives probabilities. There is no other form of reasoning. "Induction" and "abduction" are pre-Bayesian gropings in the dark, of no more account than the theory of humours in medicine.

"Research taste" is .

This is partly a terminology issue. By "controlling a variable" I mean "taking actions as necessary to keep that variable at some reference level." So I say that the thermostat is controlling the temperature of the room (or if you want to split hairs, the temperature of the temperature sensor—suitably siting that sensor is an important part of a practical system). In the same sense, the body controls its core temperature, its blood oxygenation level, its posture^[1], and many other things, and its actions to obtain those ends include sweating, breathing, changing muscle tensions, etc.

By the "output" or "action" of a control system I mean the actions it takes to keep the controlled variable at the reference. For the thermostat, this is turning the heat source on and off. It is not "controlling" (in the sense I defined) the rate of adding heat. The thermostat does not know how much heat is being delivered, and does not need to.

The resulting behaviour of the system is to keep the temperature of the room between two closely spaced levels: the temperature at which it turns the heat on, and the slightly higher temperature at which it turns the heat off. The rate at which the temperature goes up or down does not matter, provided the heat source is powerful enough to replenish all the energy leaking out of the walls, however cold it gets outside. If the heat source were replaced by one delivering twice as much power, the performance of the thermostat would be unchanged, except for being able to cope with more extreme cold weather.

The only delays in the thermostat itself are the time it takes for a mechanical switch to operate (milliseconds) and the time it takes for heat production to reach the sensor (minutes). These are so much faster than the changes in temperature due to the weather outside that it is most simply treated as operating in continuous time. There would be no practical benefit from sampling the temperature discretely and seeing how slow a sample rate you can get away with.

With a good model

There's the rub. Your model will have to not only know the external temperature, but also the conductivity of the walls, the power delivered or extracted by the heat/cold source, the people or pet animals in the room and how much heat they are generating, the temperature in the adjoining rooms, and all the other factors affecting the temperature that the designer may not have thought of.

All to avoid the cost of a thermometer which you'll need anyway to calibrate the model. This is Heath Robinson, not practical engineering.