  We introduce a new procedure for iterative selection of determinant spaces
capable of describing highly correlated systems. This adaptive configuration
interaction (ACI) determines an optimal basis by an iterative procedure in
which the determinant space is expanded and coarse grained until self
consistency. Two importance criteria control the selection process and tune the
ACI to a user-defined level of accuracy. The ACI is shown to yield potential
energy curves of N$_2$ with nearly constant errors, and it predicts
singlet-triplet splittings of acenes up to decacene that are in good agreement
with the density matrix renormalization group.
