The onset of competition coupled with the increasingly networked nature of societies and their supporting economies implies that the extant static planning approaches are no longer adequate. Uncertainties, arising from climactic, political and economic changes, suggest the need for robust solutions while resource management questions have taken on a competitive overtone with multiple users vying for scarce resources. In effect, the question of interest has shifted from that of finding the best solution to one of determining an equilibrium in user strategies; a set of decisions from which no user has a desire to deviate. In a nutshell, this study focuses on the theory and algorithms for addressing problems lying at the nexus of competition, uncertainty and dynamics. The work will find application in the design, control, operation and simulation of large networked markets.
This work addresses theoretical and methodological questions underlying the solution of game-theoretic problems in settings complicated by uncertainty and dynamics. More specifically, we focus on stochastic dynamic equilibrium problems, particularly stochastic Nash and Stackelberg equilibrium problems as well as their dynamical extensions. Truly large-scale instances will be addressed by asynchronous grid-computing extensions. A strong component of this research lies in the involvement of both undergraduate students as well as those from under-represented groups. Another important component of this research program will be the timely posting of all the results (theory, algorithms and software) obtained on a dedicated website, so that the research output can be parlayed to other researchers, practitioners, and industry, and thus can have a much broader impact in educational and industrial sectors on a global scale.
