1) We don't need an unbounded utility function to demonstrate Pascal's Mugging. Plain old large numbers like 10^100 are enough.
2) It seems reasonable for utility to be linear in things we care about, e.g. human lives. This could run into a problem with non-uniqueness, i.e., if I run an identical computer program of you twice, maybe that shouldn't count as two. But I think this is sufficiently murky as to not make bounded utility clearly correct.
Thanks for this. And thanks also for the pointer to Scott's guide.
Did you do any testing pre-pregnancy, i.e. for genetic matchup between you and your husband? And did you do any of the fetal testing mentioned e.g. for autism? Wondering about the cost-benefit on those.
I finished my math PhD thesis in September!
Indeed, conservation laws correspond to symmetries: http://en.wikipedia.org/wiki/Noether%27s_Theorem
Along with the other physics-related examples here, Richard Dawkins' pendulum video seems relevant here: http://www.youtube.com/watch?v=Bsk5yPFm5NM
I was like this from ages 12-18, perhaps? It started because quite a few people actually were mean to me, but my brain incorrectly extrapolated and assumed everyone was. The beginning of the end was when I started to do something that I had defined as the province of the liked-people (in this case, dating), though it took about two years to purge the habit.
Perhaps there is something you are similarly defining to imply likedness, and you can do that thing.
Monologues or disjointed verbal fragments. When I am mad at someone (hasn't really happened for a few years :) ) I get into dialogues with them, usually going in circles.
For a teaser, the part about singing logarithms looks cool.
Is this actually incorrect, though? As far as I know, people have problems and inadequacies. When they solve them, they move on to worrying about other things. It's probably a safe bet that the awesome people you're describing do as well.
What probably is wrong is that general awesomeness makes hidden bad stuff more likely.
Rolling all 60 years of bets up into one probability distribution as in your example, we get:
I think what this shows is that the aggregating technique you propose is no different than just dealing with a 1-shot bet. So if you can't solve the one-shot Pascal's mugging, aggregating it won't help in general.