Nothing much happens to intelligent agents—because an intelligent agents’ original priors mostly get left behind shortly after they are born—and get replaced by evidence-based probability estimates of events happening.
Prior determines how evidence informs your estimates, what things you can consider. In order to “replace priors with evidence-based probability estimates of events”, you need a notion of event, and that is determined by your prior.
Prior evaluates, but it doesn’t dictate what is being evaluated. In this case, “events happening” refers to subjective anticipation, which in turn refers to prior, but this connection is far from being straightforward.
“Determined” in the sense of “weakly influenced”. The more actual data you get, the weaker the influence of the original prior becomes—and after looking at the world for a little while, your original priors become insignificant—swamped under a huge mountain of sensory data about the actual observed universe.
Priors don’t really affect what things you can consider—since you can consider (and assign non-zero probability to) receiving any sensory input sequence.
I use the word “prior” in the sense of priors as mathematical objects, meaning all of your starting information plus the way you learn from experience.
I can’t quite place “you need a notion of event, and that is determined by your prior”, but I guess the mapping between sample space and possible observations is what you meant.
Well yes, you have “priors” that you learn from experince. An uncomputable world is not a problem for them—since you can learn about uncomputable physics, the same way as you learn about everything else.
This whole discussion seems to be a case of people making a problem out of nothing.
Well yes, you can have “priors” that you have learned from experience. An uncomputable world is not a problem in that case either—since you can learn about uncomputable physics, in just the same way that you learn about everything else.
This whole discussion seems to be a case of people making a problem out of nothing.
Prior determines how evidence informs your estimates, what things you can consider. In order to “replace priors with evidence-based probability estimates of events”, you need a notion of event, and that is determined by your prior.
Prior evaluates, but it doesn’t dictate what is being evaluated. In this case, “events happening” refers to subjective anticipation, which in turn refers to prior, but this connection is far from being straightforward.
“Determined” in the sense of “weakly influenced”. The more actual data you get, the weaker the influence of the original prior becomes—and after looking at the world for a little while, your original priors become insignificant—swamped under a huge mountain of sensory data about the actual observed universe.
Priors don’t really affect what things you can consider—since you can consider (and assign non-zero probability to) receiving any sensory input sequence.
I use the word “prior” in the sense of priors as mathematical objects, meaning all of your starting information plus the way you learn from experience.
I can’t quite place “you need a notion of event, and that is determined by your prior”, but I guess the mapping between sample space and possible observations is what you meant.
Well yes, you have “priors” that you learn from experince. An uncomputable world is not a problem for them—since you can learn about uncomputable physics, the same way as you learn about everything else.
This whole discussion seems to be a case of people making a problem out of nothing.
Well yes, you can have “priors” that you have learned from experience. An uncomputable world is not a problem in that case either—since you can learn about uncomputable physics, in just the same way that you learn about everything else.
This whole discussion seems to be a case of people making a problem out of nothing.