  We present a best-response based algorithm for computing verifiable
$\varepsilon$-perfect Bayesian equilibria for sequential auctions with
combinatorial bidding spaces and incomplete information. Previous work has
focused only on computing Bayes-Nash equilibria for static single-round
auctions, which our work captures as a special case. Additionally, we prove an
upper bound $\varepsilon$ on the utility loss of our approximate equilibria and
present an algorithm to efficiently compute $\varepsilon$ based on the
immediate loss at each subgame. We evaluate the performance of our algorithm by
reproducing known results from several auctions previously introduced in the
literature, including a model of combinatorial split-award auctions used in
procurement.
