@mastersthesis {1500064,
	title = {Information as a Double-Edged Sword in Strategic Interactions },
	year = {2018},
	type = {PhD thesis},
	abstract = {This thesis considers the following question: in systems with self-interested agents (a.k.a.,games), how does information {\textemdash} i.e., what each agent knows about their environment and otheragents{\textquoteright} preferences {\textemdash} affect their decision making? The study of the role of information ingames has a rich history, and in fact forms the celebrated field of information economics. However, different from previous descriptive study, this thesis takes a prescriptive approach and examines computational questions pertaining to the role of information. In particular, it illustratesthe double-edged role of information through two threads of research: (1) how to utilize information to one{\textquoteright}s own advantage in strategic interactions; (2) how to mitigate losses resulting frominformation leakage to an adversary. In each part, we study the algorithmic foundation of basicmodels and also develop efficient solutions to real-world problems arising from physical securitydomains. Besides pushing the research frontier, the work of this thesis is also directly impactingseveral real-world applications, resulting in delivered software for improving the scheduling ofUS federal air marshals and the design of patrolling routes for wildlife conservation.More concretely, the first part of this thesis studies an intrinsic phenomenon in human endeavors termed persuasion {\textemdash} i.e., the act of exploiting an informational advantage in order toinfluence the decisions of others. We start with two real-world motivating examples, illustratinghow security agencies can utilize an informational advantage to influence adversaries{\textquoteright} decisionsand deter potential attacks. Afterwards, we provide a systematic algorithmic study for the foundational economic models underlying these examples. Our analysis not only fully resolves thecomplexity of these models, but also leads to new economic insights. We then leverage the insights and algorithmic ideas from our theoretical analysis to develop new models and solutionsfor concrete real-world security problems.The second part of this thesis studies the other side of the double-edged sword, namely, howto deal with disadvantages due to information leakage. We also start with real-world motivatingexamples to illustrate how classified information about security measures may leak to the adversary and cause significant loss to security agencies. We then propose different models to captureinformation leakage based on how much the security agency is aware of the leakage situation,and provide thorough algorithmic analysis for these models. Finally, we return to the real-worldproblems and design computationally efficient algorithms tailored to each security domain.},
	author = {Haifeng Xu}
}
