On Design and Analysis of Cyber-Physical Systems with Strategic Agents
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In contrast to traditional Cyber-Physical Systems (CPS) where a designer specifies an action plan for every component of the system, in CPS with strategic agents, every agent behave selfishly and chooses his strategy privately so as to maximize his own objective. In this presentation, we study problems arising in the design and analysis of CPS with strategic agents.
We consider two classes of design problems with applications to power systems and transportation networks. In the first class, the designer utilizes her control over decisions and resources in the system to incentivize the agents via monetary incentives to reveal their private information that is crucial for the operation of the system. In the second class, the designer utilizes her informational advantage over the agents and employ informational incentive mechanisms to influence the agents' decisions.
We study the analysis of CPS with strategic agents as a stochastic dynamic game of asymmetric information. We present a set of conditions sufficient to characterize an information state for each agent. This information state provides a sufficient statistic for decision-making purposes in strategic and non-strategic settings. The proposed approach generalizes and unifies the existing results for dynamic teams with non-classical information structure and dynamic games with asymmetric information.