UC Santa Barbara

Strategic interactions in multi-agent systems can be conveniently modeled, manipulated and characterized within the analytical framework provided by game theory and mechanism design, and used to extract engineering insights regarding systems of interest. Accordingly, in this dissertation, we adopt such a framework and pursue research directions aimed at understanding how information and externalities impact the strategic outcomes that can emerge in systems with multiple, non-cooperative decision makers. We consider two types of mechanisms: decision-based mechanisms and preference-based mechanisms which respectively manipulate either the players' action sets or the players' utilities -- the two major building blocks of a game. We conduct our analysis of decision-based mechanisms on Colonel Blotto games which are popular models for competitive resource allocation in adversarial environments. Within this framework, we first consider settings where the information to a competitor is obfuscated, and quantify the value of information relating to competitive objectives and the opponent's strength. We then consider the role of pre-emption under this framework, and show that -- perhaps surprisingly -- revealing information to competitors can also offer strategic benefits in competitive interactions. Our results on preference-based mechanisms focus on the design of taxes in congestion games to optimize the system performance. In our study, we consider three performance measures corresponding with the worst-case equilibrium efficiency (Price of Anarchy), the best-case equilibrium efficiency (Price of Stability), and the transient system performance (Price of Urgency). Within this context, our first set of results focus on optimizing the Price of Anarchy; we derive tractable methodologies for computing the optimal taxes within this setting. We then investigate the consequences of optimizing for the worst case on the other performance measures: we show that the taxes that optimize the Price of Anarchy necessarily have Price of Stability equal to the Price of Anarchy, and that optimal Price of Anarchy guarantees can correspond with arbitrarily poor Price of Urgency. We supplement this last set of results by proposing techniques for characterizing the respective trade-off curves. We conclude with a discussion on future directions for both decision- and preference-based mechanisms.