Game theory has long been used as a powerful tool to model and analyze the outcomes of interactions between agents with conflicting goals and preferences. The recent confluence of game theory with computational systems has spurred research on the role of information in games. At a high level, agents' behavior in a strategic interaction will necessarily be based on the information they have available, as well as their beliefs about the information held by others. Traditionally, in economics, these information structures have been assumed to be exogenous; that is, the information structure is given, and the analysis departs from there.
With few exceptions, it has only been recently that research has focused on the acquisition and revelation of information as part of the game itself. A key motivation here is that information is often produced at a cost to those who produce it, meaning that the acquisition of information requires rewards of selfish agents, a typical situation requiring game-theoretic viewpoints. Similarly, one or more agents possessing information may find it beneficial to strategically reveal some or all of it to other agents to induce particular behaviors, benefiting the agent, or society as a whole. In both cases, designing optimal or near-optimal mechanisms for acquiring or revealing information is challenging, and requires the combination of game-theoretic and algorithmic insights.
This project will analyze the role of information acquisition and revelation in games. Specifically, it will study the following algorithmic problems: (1) Optimal information acquisition by a central authority from selfish agents (under several natural models); and (2) optimal information revelation by a central authority to selfish agents (under several natural models and information structures).
The proposed research will help to further our understanding of the role of information in games, by providing fundamental characterizations of what is and is not achievable in terms of its acquisition and revelation. The algorithms to be developed also have the potential to impact the way online auctions are conducted, where information (or lack thereof) plays a central role.
The PI and co-PI both have a long-standing commitment to active dissemination of results and community building going beyond mere publications. They have created and will continue to create interdisciplinary graduate courses and make detailed class notes available for use by other instructors. They will also actively establish the area by giving tutorials at major conferences and producing overview articles for a broader audience. The PI and co-PI are committed to including undergraduates in the research effort, with a particular effort to recruit women and underrepresented minorities. The PI will also continue to help build a strong computer science and problem solving community by organizing local programming contests and significantly strengthening the computer science curriculum at USC.
