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When preferences are selfless, anthropic problems are easily solved by a change of perspective. For example, if we do a Sleeping Beauty experiment for charity, all Sleeping Beauty has to do is follow the strategy that, from the charity's perspective, gets them the most money. This turns out to be an easy problem to solve, because the answer doesn't depend on Sleeping Beauty's subjective perception.
But selfish preferences - like being at a comfortable temperature, eating a candy bar, or going skydiving - are trickier, because they do rely on the agent's subjective experience. This trickiness really shines through when there are actions that can change the number of copies. For recent posts about these sorts of situations, see Pallas' sim game and Jan_Ryzmkowski's tropical paradise. I'm going to propose a model that makes answering these sorts of questions almost as easy as playing for charity.
To quote Jan's problem:
It's a cold cold winter. Radiators are hardly working, but it's not why you're sitting so anxiously in your chair. The real reason is that tomorrow is your assigned upload, and you just can't wait to leave your corporality behind. "Oh, I'm so sick of having a body, especially now. I'm freezing!" you think to yourself, "I wish I were already uploaded and could just pop myself off to a tropical island."
And now it strikes you. It's a weird solution, but it feels so appealing. You make a solemn oath (you'd say one in million chance you'd break it), that soon after upload you will simulate this exact scene a thousand times simultaneously and when the clock strikes 11 AM, you're gonna be transposed to a Hawaiian beach, with a fancy drink in your hand.
It's 10:59 on the clock. What's the probability that you'd be in a tropical paradise in one minute?
Just as computer programs or brains can split, they ought to be able to merge. If we imagine a version of the Ebborian species that computes digitally, so that the brains remain synchronized so long as they go on getting the same sensory inputs, then we ought to be able to put two brains back together along the thickness, after dividing them. In the case of computer programs, we should be able to perform an operation where we compare each two bits in the program, and if they are the same, copy them, and if they are different, delete the whole program. (This seems to establish an equal causal dependency of the final program on the two original programs that went into it. E.g., if you test the causal dependency via counterfactuals, then disturbing any bit of the two originals, results in the final program being completely different (namely deleted).)
So, the standard Bayesian analogue of Solomonoff induction is to put a complexity prior over computable predictions about future sensory inputs. If the shortest program outputting your predictions looks like a specification of a physical world, and then an identification of your sensory inputs within that world, and the physical world in your model has both a meatspace copy of you and a simulated copy of you, the only difference in this Solomonoff-analogous prior between being a meat-person and a chip-person is the complexity of identifying your sensory inputs. I think it is unfounded substrate chauvinism to think that your sensory inputs are less complicated to specify than those of an uploaded copy of yourself.
Firstly, this isn't a Solomonoff-analogous prior. It is the Solomonoff prior. Solomonoff Induction is Bayesian.
Secondly, my objection i... (read more)