  Stackelberg equilibrium is a solution concept in two-player games where the
leader has commitment rights over the follower. In recent years, it has become
a cornerstone of many security applications, including airport patrolling and
wildlife poaching prevention. Even though many of these settings are sequential
in nature, existing techniques pre-compute the entire solution ahead of time.
In this paper, we present a theoretically sound and empirically effective way
to apply search, which leverages extra online computation to improve a
solution, to the computation of Stackelberg equilibria in general-sum games.
Instead of the leader attempting to solve the full game upfront, an approximate
"blueprint" solution is first computed offline and is then improved online for
the particular subgames encountered in actual play. We prove that our search
technique is guaranteed to perform no worse than the pre-computed blueprint
strategy, and empirically demonstrate that it enables approximately solving
significantly larger games compared to purely offline methods. We also show
that our search operation may be cast as a smaller Stackelberg problem, making
our method complementary to existing algorithms based on strategy generation.
