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.
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.
Firstly, this isn't a Solomonoff-analogous prior. It is the Solomonoff prior. Solomonoff Induction is Bayesian.
Secondly, my objection i...
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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: