The subject of this paper is to estimate adaptively the common probability
density of n independent, identically distributed random variables. The
estimation is done at a fixed point $x_{0}\in \mathbb R$
, over the density
functions that belong to the Sobolev class Wn(β,L). We consider the
adaptive problem setup, where the regularity parameter β is unknown
and varies in a given set Bn. A sharp adaptive estimator is obtained,
and the explicit asymptotical constant, associated to its rate of
convergence is found.