Analysis and Design of Information Transmission in Networks of Strategic Agents
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Most of today’s systems consist of strategic/selfish agents with some private information and uncertainty towards others’ information and system states. Transmission and exchange of information in such networks have been the focus of many interesting research areas such as mechanism design, information design, and Bayesian learning. The information is directly exchanged in mechanism design and information design, and the goal is to steer agents’ actions towards a desirable direction by putting incentives in place (mechanism design) or designing the appropriate information structure (information design). Information can also be spread more indirectly by agents who observe each other’s actions (Bayesian learning).
In this thesis, we follow two main directions of “Analysis” and “Design” to investigate the spread of information in networks of strategic agents. Specifically, we analyze dynamic systems with asymmetric information and characterize their equilibria and study the spread of information induced by these equilibrium behaviors. We investigate the learning failures known as informational cascades and suggest settings to avoid them. Furthermore, we study how incentives or information structures can be designed to shape the equilibrium behavior of agents. Specifically, we design distributed mechanisms for optimal network resource allocation problems. We also study a joint information and mechanism design problem for queues with heterogeneous users.
Chair: Professor Achilleas Anastasopoulos