  We establish a general optimization framework for the design of automated
bidding agent in dynamic online marketplaces. It optimizes solely for the
buyer's interest and is agnostic to the auction mechanism imposed by the
seller. As a result, the framework allows, for instance, the joint optimization
of a group of ads across multiple platforms each running its own auction
format. Bidding strategy derived from this framework automatically guarantees
the optimality of budget allocation across ad units and platforms. Common
constraints such as budget delivery schedule, return on investments and
guaranteed results, directly translates to additional parameters in the bidding
formula. We share practical learnings of the deployed bidding system in the
LinkedIn ad marketplace based on this framework.
