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Many control applications have a decentralized structure, where each subunit has access to different information about the system state. Still, most control theory has been developed in a centralized setting, where all measurements are processed together to compute the control signals. This paradigm has conceptual advantages, but also inherent limitations in terms of complexity and integrity. The purpose of this lecture is to show how ideas from convex optimization and game theory may help to go beyond the traditional paradigm to support analysis and synthesis of distributed controllers.