  We give a $\mathrm{poly}(\log n, 1/\epsilon)$-query adaptive algorithm for
testing whether an unknown Boolean function $f: \{-1,1\}^n \to \{-1,1\}$, which
is promised to be a halfspace, is monotone versus $\epsilon$-far from monotone.
Since non-adaptive algorithms are known to require almost $\Omega(n^{1/2})$
queries to test whether an unknown halfspace is monotone versus far from
monotone, this shows that adaptivity enables an exponential improvement in the
query complexity of monotonicity testing for halfspaces.
