Dissertation Defense

Efficient operation of dynamic networked systems can significantly improve our quality of life. The operation of a dynamic networked system involves decision making processes by many decision makers (DMs) who may or may not have the same information, and may or may not share the same objective. The quality of each DM's decision depends on the quality of information available for decision-making. Since the network is dynamic, the available information is a dynamic process that depends on the DMs' decision rules. Information affects decisions, and decisions influence information. Research on the interaction between information and decisions plays a key role in determining efficient designs of modern social-technological systems.
We study the impact of the information-decision interaction on system performance within the context of: (i) centralized stochastic control; (ii) decentralized stochastic control; and (iii) stochastic dynamic games with asymmetric information. In centralized stochastic control, we discover conditions sufficient to guarantee the optimality of a myopic channel sensing policy. In decentralized stochastic control, we determine an optimal policy for decentralized routing, and an efficient decentralized protocol for multiple access communication. In dynamic stochastic games with asymmetric information, we provide a sequential decomposition of the dynamic games and an algorithm to compute equilibrium strategies.