Using these number, it appears that your expected gain is [p2 + 4(1-p)p + p(p+4(1-p))]/(2-p)
Do you mean “1+p” instead of “2-p” at the end there? If not, where does “2-p” come from?
Since there are N=2 individuals, the CDP thus cancels both the 2 and the (1+p) factors
Why do you say that (N=2), since the number of individuals is actually random? If you EXIT at X, then the individual at Y doesn’t exist, right?
Do you think CDP can be formalized sufficiently so that it can be applied mechanically after transforming a decision problem into some formal representation (like a decision tree, or world program as in UDT1)? The way it is stated now, it seems too ambiguous to say what is the solution to a given problem under CDP.
Do you mean “1+p” instead of “2-p” at the end there? If not, where does “2-p” come from?
Thanks, error corrected (I mixed up p with 1-p).
Why do you say that (N=2), since the number of individuals is actually random? If you EXIT at X, then the individual at Y doesn’t exist, right?
Because the number of individuals is exactly two—in that you have a certain probability of being either individuals. The second may not exist, but the probability of being the second is non-zero.
But I admit this is not fully rigorous; more examples are needed.
Do you think CDP can be formalized sufficiently so that it can be applied mechanically after transforming a decision problem into some formal representation (like a decision tree, or world program as in UDT1)?
I believe it can be formalized sufficiently; so far, no seeming paradox I’ve met has failed to fall eventually to these types of reasonings. However, more work needs to be done; in particular, one puzzle: why does the CDP for the absent-minded driver give you total expectation, while for Eliezer’s problem it gives you individual expectation?
Do you mean “1+p” instead of “2-p” at the end there? If not, where does “2-p” come from?
Why do you say that (N=2), since the number of individuals is actually random? If you EXIT at X, then the individual at Y doesn’t exist, right?
Do you think CDP can be formalized sufficiently so that it can be applied mechanically after transforming a decision problem into some formal representation (like a decision tree, or world program as in UDT1)? The way it is stated now, it seems too ambiguous to say what is the solution to a given problem under CDP.
Thanks, error corrected (I mixed up p with 1-p).
Because the number of individuals is exactly two—in that you have a certain probability of being either individuals. The second may not exist, but the probability of being the second is non-zero.
But I admit this is not fully rigorous; more examples are needed.
I believe it can be formalized sufficiently; so far, no seeming paradox I’ve met has failed to fall eventually to these types of reasonings. However, more work needs to be done; in particular, one puzzle: why does the CDP for the absent-minded driver give you total expectation, while for Eliezer’s problem it gives you individual expectation?
I now think I’ve got a fomalisation that works; I’ll put it up in a subsequent post.
Was this ever written up?
This is the most current version: https://www.youtube.com/watch?v=aiGOGkBiWEo