MrShaggy comments on What is control theory, and why do you need to know about it? - Less Wrong
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Certainly I, as the designer, had a model of the robot and its environment when I wrote that program, and the program implements those models. But the robot itself has no model of its environment. It calculates the positions of its feet, relative to itself, by sensing its joint angles, knowing the lengths of its limb segments and calculating, so it does have a fairly limited model of itself: it knows its own dimensions. However, it does not know its own mass, or the characteristics of its sensors and actuators.
The fact that it works does not mean that it has an "implicit" model of the environment: "implicit", in a context like this, means "not". What is a model? A model is a piece of mathematics in which certain quantities correspond to certain properties of the thing modelled, and certain mathematical relationships between these correspond to certain physical relationships. Maxwell's equations model electromagnetic phenomena. The Newton-Raphson (EDIT: I meant Navier-Stokes) equation models fluid flow. "Implicit model" is what one says, when one expects to find a model and finds none. The robot's environment contains a simulated wind pushing on the robot, and a simulated hand giving it a shove. The robot knows nothing of this: there is no variable in the part of the program that deals with the robot's sensors, actuators, and control algorithms that represents the forces acting on it. The robot no more models its environment than a thermostat models the room outside it.
Since it is possible to build systems that achieve goals without models, and also possible, but in general rather more complicated, to build such systems that do use models, I do not think that the blind god of evolution is likely to have put models anywhere. It has come up with something -- us, and probably the higher animals -- that can make models, but nothing currently persuades me that models are how brains must work. I see no need of that hypothesis.
I'd rather like to build that robot. If I did, I would very likely use an onboard computer just to have flexibility in reconfiguring its control algorithms, but the controllers themselves are just PID loops. If, having got it to work robustly, I were to hard-wire it, the control circuitry would consist of a handful of analogue components for each joint, and no computer required. I still find it remarkable, how much it can do with so little.
Could one argue the tuning by the programmer incorporates the relevant aspects of the model? (Which is what I think commenter meant by "implicit.") In my mom's old van, going down a steep hill would mess up the cruise control: as you say, if you push hard enough, you can over come a control loop's programming. So a guess as to relation to Bayescraft: certain real world scenarios operate within a narrow enough set of parameters enough of the time that one can design feedback loops that do not update based on all evidence and still work well enough.