  The information complexity of a function $f$ is the minimum amount of
information Alice and Bob need to exchange to compute the function $f$. In this
paper we provide an algorithm for approximating the information complexity of
an arbitrary function $f$ to within any additive error $\alpha > 0$, thus
resolving an open question as to whether information complexity is computable.
  In the process, we give the first explicit upper bound on the rate of
convergence of the information complexity of $f$ when restricted to $b$-bit
protocols to the (unrestricted) information complexity of $f$.
