Spaghetti code
en.wikipedia.org2 pointsby picomancer0 comments
a = 1
def contrived():
global a # I added this
a = 2
return a
contrived() # 2
a # 2
def enclose():
a = 1
def contrived():
nonlocal a
a = 2
return a
contrived() # 2
a # 2
The probabilities are initialized to some value (the "prior"), then when you pull the arm, you get some new information, which you use to update the probabilities based on evidence.
It would be interesting to try to see if you could analytically solve this problem for a simple family of distributions. For example, assume each lever produces Gaussian results, but has an unknown mean and SD. Set the prior to be that the means are normally distributed with mean 0 and SD 1, and the SD's are exponentially distributed with mean 1.