I see, thanks. IMO the two are indeed quite similar but I think my example illustrates the problem of self-location uncertainty in a clearer way. That being said, what is your thought on the probability of getting a lollipop if you’re in such a scenario? Are the odds 1:1 or 1001:1?
Right, so your perspective is that due to the multiple embeddings of yourself being in the heads scenario, it is the 1001:1 option. That line of reasoning is kind of what I thought as well, but it was against the 1:1 odds as would be suggested by my intuition. I guess this is the same as the halfer vs thirder debate, where 1:1 is the halfer position and the 1001:1 is the thirder position.
I suppose the lollipops are indeed an unnecessary addition, so the final question can really be reframed as “what is the probability that you will see heads?”
You don’t need a coin flip, I’m fine with lollipops randomly given to 1000 out of 1001 participants. This is not about “being in the head”, this is an experimental result, assume you run a large number of experiments like that. The stipulation is that it is impossible to tell from the inside if it is a simulation or the original, so one has to use the uniform prior.
Not an expert, either, hah. But yeah, what I meant is that the distribution is uniform over all instances, whether originals or copies, since there is no way to distinguish internally between the twem.
I see, thanks. IMO the two are indeed quite similar but I think my example illustrates the problem of self-location uncertainty in a clearer way. That being said, what is your thought on the probability of getting a lollipop if you’re in such a scenario? Are the odds 1:1 or 1001:1?
I don’t see a difference between your scenario and 1000 of 1001 people randomly getting a lollipop, no coin flip needed, no simulation and no cloning.
Right, so your perspective is that due to the multiple embeddings of yourself being in the heads scenario, it is the 1001:1 option. That line of reasoning is kind of what I thought as well, but it was against the 1:1 odds as would be suggested by my intuition. I guess this is the same as the halfer vs thirder debate, where 1:1 is the halfer position and the 1001:1 is the thirder position.
I suppose the lollipops are indeed an unnecessary addition, so the final question can really be reframed as “what is the probability that you will see heads?”
You don’t need a coin flip, I’m fine with lollipops randomly given to 1000 out of 1001 participants. This is not about “being in the head”, this is an experimental result, assume you run a large number of experiments like that. The stipulation is that it is impossible to tell from the inside if it is a simulation or the original, so one has to use the uniform prior.
Ah I see. Sorry for not being too familiar with the lingo but does uniform prior just mean equal probability assigned to each possible embedding?
Not an expert, either, hah. But yeah, what I meant is that the distribution is uniform over all instances, whether originals or copies, since there is no way to distinguish internally between the twem.