alex_zag_al

Lately I've been reading a lot about the problem of logical uncertainty. The problem is that there are logical consequences of your beliefs that you're uncertain about. So, for statements like "the billionth digit of pi is even", it's provable from your beliefs. But you're still uncertain of it. So, the problem is, what's its probability? Well, 1/2, probably, but from what principled theory can you derive that? That's the question. What probabilities we should assign to logical statements, and what laws of probability apply to them. With all the time I've been spending on it, I've been wondering, will I ever have the opportunity to use it? My conclusion is, probably not me, personally. But I have come up with a decent list of ways other people might use it. Combining information from simulation and experiment This is why I first became interested in the problem--I was working in protein structure prediction. The problem in protein structure prediction is figuring out how the protein folds. A protein is a big molecule. They're always these long, linear chains of atoms with relatively short side-branches. Interestingly, there are easy experiments to learn what they'd look like all stretched out in a line like this. But in reality, this long chain is folded up in a complex way. So, the problem is: given the linear, stretched out structure, what's the folded structure? We have two general approaches to solve this problem. One is a physics calculation. A protein folds because of electromagnetic forces, and we know how those work. So, you can set up a quantum physics simulation and end up with the correct fold. But you won't really end up with anything because your simulation will never finish if you do it precisely. So a lot of work goes into coming up with realistic approximate calculations, and using bigger computers. (Or distributed computing - Rosetta@Home distributes the calculations over the idle time of people's home computers, and you can download it now