Demystifier said:
Fundamental are those basic rules that cannot be violated even in principle.
This is how I think of this. For me it helps to think of two forms of probabilities, these two versions are also what I take to illustrated the difference between correlation and causation in agent view. The first type is just correlation, the second type is what is "causes" actions. The feedback loop between the two would be more complex though.
1) Correlations - or distributional patterns in the agents or physicists raw observations.
For example the final results from many many trials in particle experiments, where you get an observed "probability" corresponding to the whole ensemble (never individual events). Without an explicit history of measurment records, this "probability" can not be established. This is what one measures in a real experiments. Inferring observed distributions, does not require born rule. In an abstract agent one could envision and event counter, and automatically builds up a frequentist distribution. It requires not "inferences", just observation and counting distinguishable events.
2) Expectations of the agent - that influences the agents instant action.
This is not based on measurements, and this is where the QM inferemnce comes in. It's based on the agents internal inference (expectation) of the future trial, based on it's own encoded (possibly lossy) information. (Or the "initial state" or "preparation") This kind of "probability" would ideally influence the choices made by the agent, in case it was interacting more than a normal "measurement device does". This is that requires the use of the born rule. As it the prescribed rule for constructing the p-value from the abstract reprensentation of the information (quantum state). Thus I imagine this born rule to be value also for closed systems (ie given that we take quantum theory for what it is), because it describes how the agents "aligns" even in between measurements.
Other than this, we expect that if the theory is GOOD, then the two probabilities (ie it's numbers) will agree!
Ie. the theories "expectated" probabiltiy, should match the observed one.
=> For this we need real measurements (and thus "open" up the system), yet the born rule does make sense for closed systems as it prescribes the inference on the agent side - not on the quantum side.
But I think it's helpful, to understand this, if one sees that they are really different, and don't HAVE to agree. Because the physical process of inference from current state, and the observational recordes are two different ones). It's when they do not agree, that we have the input for a learning loop? So I don't think one should think that a theory whose expectations fails to be equal to the actual future, is useless or wrong. I think there is a value to see how it is instead part of the game, and the theory is alive.
What makes the above indeed possible seems like hopeless soup, is that we do not yet know how, observational history "forges" the agents internal states, that implies the expectations. Ie how the "internal state" revision works. It's clearly not a simlpy bayesian update, as several non-commuting observables must be combinied into ONE state, and ontop of this makes this with the capacity the agent has at hand. But this is exactly what i personally take to be one of the key quests for the foundations. Smolin talked about "
principle of precedence" which is just indicative of the idea, but I find this to be a largely crazy and immature field, but still extremely interesting and impossible to get off your mind.
/Fredrik