Source: J. Appl. Probab. Volume 42, Number 1
(2005), 108-120.
Let X1, X2,...,
Xn be independent, identically
distributed random variables, uniform on [0,1]. We observe the
Xk sequentially and must stop on exactly
one of them. No recollection of the preceding observations is
permitted. What stopping rule τ minimizes the expected rank
of the selected observation? This full-information expected-rank
problem is known as Robbins' problem. The general solution
is still unknown, and only some bounds are known for the limiting
value as n tends to infinity. After a short discussion of
the history and background of this problem, we summarize what is
known. We then try to present, in an easily accessible form, what
the author believes should be seen as the essence of the more
difficult remaining questions. The aim of this article is to evoke
interest in this problem and so, simply by viewing it from what
are possibly new angles, to increase the probability that a reader
may see what seems to evade probabilistic intuition.
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