Teams refer to multi-agent decision problems where all agents have a common objective (either to minimize a shared cost function or to maximize a shared utility function). Such models arise in various applications including networked control systems, communication networks, sensor networks, robotics, and smart grids. A key feature of such models is information decentralization---i.e., different agents have different information about the state of the network. Information decentralized leads to the signaling aspect of control: in addition to understanding how their actions affect the state evolution and state estimation, agents also need to understand how other agents will interpret and react to their actions.
In this talk I will present an overview of the current state of the art in sequential dynamic teams and highlight applications in networked control systems and real-time communication. I will conclude the talk with some thoughts on the future directions in this area.
Coffee and biscuits will be offered at the beginning of the seminar.
Welcome to everyone!