But that's a fix to a global problem that you won't fix anyway. What you can do is allocate some resources to fixing a lesser problem "this guy had nothing to eat today".
It seems to me that your argument proves too much -- when faced with a problem that you can fix you can always say "it is a part of a bigger problem that I can't fix" and do nothing.
What do you mean by 'real fix' here? What if said that real-real fix requires changing human nature and materialization of food and other goods out of nowhere? That might be more effective fix, but it is unlikely to happen in near future and it is unclear how you can make it happen. Donating money now might be less effective, but it is somehow that you can actually do.
Detailed categorizations of mental phenomena sounds useful. Is there a way for me to learn that without reading religious texts?
How can you check proof of any interesting statement about real world using only math? The best you can do is check for mathematical mistakes.
I assume you mean that I assume P(money in Bi | buyer chooses Bi )=0.25? Yes, I assume this, although really I assume that the seller's prediction is accurate with probability 0.75 and that she fills the boxes according to the specified procedure. From this, it then follows that P(money in Bi | buyer chooses Bi )=0.25.
Yes, you are right. Sorry.
Why would it be a logical contradiction? Do you think Newcomb's problem also requires a logical contradiction?
Okay, it probably isn't a contradiction, because the situation "Buyer writes his decision and it is common... (read more)
I've skimmed over the beginning of your paper, and I think there might be several problems with it.
I've skimmed over A Technical Explanation of Technical Explanation (you can make links end do over stuff by selecting the text you want to edit (as if you want to copy it); if your browser is compatible, toolbar should appear). I think that's the first time in my life when I've found out that I need to know more math to understand non-mathematical text. The text is not about Bayes' Theorem, but it is about application of probability theory to reasoning, which is relevant to my question. As far as I understand, Yudkowski writes about the same algorithm that... (read more)
That's interesting. I've heard about probabilistic modal logics, but didn't know that not only logics are working towards statisticians, but also vice versa. Is there some book or videocourse accessible to mathematical undergraduates?
This formula is not Bayes' Theorem, but it is a similar simple formula from probability theory, so I'm still interested in how you can use it in daily life.Writing P(x|D) implies that x and D are the same kind of object (data about some physical process?) and there are probably a lot of subtle problems in defining hypothesis as a "set of things that happen if it is true" (especially if you want to have hypotheses that involve probabilities). Use of this formula allows you to update probabilities you prescribe to hypotheses, but it is no... (read more)
The above formula is usually called "odds form of Bayes formula". We get the standard form P(x|D)=P(x)×P(D|x)P(D) by letting y=D in the odds form, and we get the odds form from the standard form by dividing it by itself for two hypotheses (P(D) cancels out).
The serious problem with the standard form of Bayes is the P(D) term, which is usually hard to estimate (as we don't get to choose what D is). We can try to get rid of it by expanding P(D)=P(D|x)P(x)+P(D|¬x)P(¬x), but that's also no good, because now we need to know P(D|¬x). One way to state the problem... (read more)