Oh, yeah. I think I was a bit confused in what I said. I wanted to highlight the difference between a short binary string, and a really complicated video feed, which probably requires a pretty decent model of the environment and which would probably benefit a lot from the knowledge that a human brain has.
I think the crux for me is less whether a specific human brain is a good choice for the UTM, and more that for any given input-history I have, I can construct a UTM such that the description length of that input-history is arbitrarily short, and so the choice of UTM is really really important in any “practical” scenario.
Given that, there must be some other argument for what we should choose as the UTM, probably so that short inputs into that UTM roughly correspond with our intuitions for simplicity. The two choices here that I feel tend to result in things that roughly match my natural intuition for elegance is either a programming-language interpreter, or a human brain, though the later one feels weirdly circular. Hence the question of whether that’s even a valid construction.
(Note: This has already been helpful in helping me think through this, so thank you! :) )
I see how the human brain based computer would give an advantage in encoding a video feed. I still don’t see how this relates to the witch hypothesis. You still have to say what the witch did and why that got you the video feed you got, right? The witch hypothesis will most likely only beat the best possible causal model if there actually is magic going on (though, there is a problem in that you might not know the best possible causal model).
If the human can execute arbitrary programs and is computable, and can interpret messages of the form “run this program on the rest of the message”, then by definition the human brain based computer is a UTM, so it can be used in Solomonoff induction, weirdly enough. However, there is a concern in that the UTM is meant to be a prior, whereas the brain is more of a representation of a posterior. So it will be able to overfit things you already know. This might not be a problem if you were using CDT but would be a problem for UDT, since UDT isn’t supposed to change its prior as it gets more observations (this would make it stop caring about non-actual worlds in e.g. counterfactual mugging, leading to dynamic inconsistency).
In general if you’re using UDT then your choice of prior is a choice of which possible worlds you care about and how much. There won’t be universally compelling arguments for a particular prior the same way there aren’t universally compelling arguments for particular values.
(also, you’re welcome, this was useful to think about from my end too!)
I think the last paragraph was the most clarifying to me in the exchange so far. If you would be up for it, I think it would be great if you could edit your top-level comment to include that paragraph and maybe also some of the other things said in this thread (though obviously no obligation, just seems better for future people who might have a similar question, to have everything in one top-level place).
Oh, yeah. I think I was a bit confused in what I said. I wanted to highlight the difference between a short binary string, and a really complicated video feed, which probably requires a pretty decent model of the environment and which would probably benefit a lot from the knowledge that a human brain has.
I think the crux for me is less whether a specific human brain is a good choice for the UTM, and more that for any given input-history I have, I can construct a UTM such that the description length of that input-history is arbitrarily short, and so the choice of UTM is really really important in any “practical” scenario.
Given that, there must be some other argument for what we should choose as the UTM, probably so that short inputs into that UTM roughly correspond with our intuitions for simplicity. The two choices here that I feel tend to result in things that roughly match my natural intuition for elegance is either a programming-language interpreter, or a human brain, though the later one feels weirdly circular. Hence the question of whether that’s even a valid construction.
(Note: This has already been helpful in helping me think through this, so thank you! :) )
I see how the human brain based computer would give an advantage in encoding a video feed. I still don’t see how this relates to the witch hypothesis. You still have to say what the witch did and why that got you the video feed you got, right? The witch hypothesis will most likely only beat the best possible causal model if there actually is magic going on (though, there is a problem in that you might not know the best possible causal model).
If the human can execute arbitrary programs and is computable, and can interpret messages of the form “run this program on the rest of the message”, then by definition the human brain based computer is a UTM, so it can be used in Solomonoff induction, weirdly enough. However, there is a concern in that the UTM is meant to be a prior, whereas the brain is more of a representation of a posterior. So it will be able to overfit things you already know. This might not be a problem if you were using CDT but would be a problem for UDT, since UDT isn’t supposed to change its prior as it gets more observations (this would make it stop caring about non-actual worlds in e.g. counterfactual mugging, leading to dynamic inconsistency).
In general if you’re using UDT then your choice of prior is a choice of which possible worlds you care about and how much. There won’t be universally compelling arguments for a particular prior the same way there aren’t universally compelling arguments for particular values.
(also, you’re welcome, this was useful to think about from my end too!)
I think the last paragraph was the most clarifying to me in the exchange so far. If you would be up for it, I think it would be great if you could edit your top-level comment to include that paragraph and maybe also some of the other things said in this thread (though obviously no obligation, just seems better for future people who might have a similar question, to have everything in one top-level place).