Approximability of combinatorial problems with multi-agent submodular cost functions

Abstract

Applications in complex systems such as the Internet have spawned a recent interest in studying situations involving multiple agents with their individual cost or utility functions. In this paper, we introduce an algorithmic framework for studying combinatorial optimization problems in the presence of multiple agents with submodular cost functions. We study several fundamental covering problems in this framework and establish upper and lower bounds on their approximability.