  Independent set is a fundamental problem in combinatorial optimization. While
in general graphs the problem is essentially inapproximable, for many important
graph classes there are approximation algorithms known in the offline setting.
These graph classes include interval graphs and geometric intersection graphs,
where vertices correspond to intervals/geometric objects and an edge indicates
that the two corresponding objects intersect.
  We present dynamic approximation algorithms for independent set of intervals,
hypercubes and hyperrectangles in $d$ dimensions. They work in the fully
dynamic model where each update inserts or deletes a geometric object. All our
algorithms are deterministic and have worst-case update times that are
polylogarithmic for constant $d$ and $\epsilon> 0$, assuming that the
coordinates of all input objects are in $[0, N]^d$ and each of their edges has
length at least 1. We obtain the following results:
  $\bullet$ For weighted intervals, we maintain a $(1+\epsilon)$-approximate
solution.
  $\bullet$ For $d$-dimensional hypercubes we maintain a
$(1+\epsilon)2^{d}$-approximate solution in the unweighted case and a
$O(2^{d})$-approximate solution in the weighted case. Also, we show that for
maintaining an unweighted $(1+\epsilon)$-approximate solution one needs
polynomial update time for $d\ge2$ if the ETH holds.
  $\bullet$ For weighted $d$-dimensional hyperrectangles we present a dynamic
algorithm with approximation ratio $(1+\epsilon)\log^{d-1}N$.
