Auction-Based Scheduling

Sequential decision-making tasks often require satisfaction of multiple, partially-contradictory objectives. Existing approaches are monolithic, where a single policy fulfills all objectives. We present auction-based scheduling, a decentralized framework for multi-objective sequential decision making. Each objective is fulfilled using a separate and independent policy. Composition of policies is performed at runtime, where at each step, the policies simultaneously bid from pre-allocated budgets for the privilege of choosing the next action. The framework allows policies to be independently created, modified, and replaced. We study path planning problems on finite graphs with two temporal objectives and present algorithms to synthesize policies together with bidding policies in a decentralized manner. We consider three categories of decentralized synthesis problems, parameterized by the assumptions that the policies make on each other. We identify a class of assumptions called assume-admissible for which synthesis is always possible for graphs whose every vertex has at most two outgoing edges.