In real life situations, most decisions are made in a dynamic context in the sense that multi-period decisions influence the final outcomes. The games of "chess" and "go" are simple examples. The main aim of this program is to study game theory, mechanism design and matching in a dynamic context. First, for dynamic games with complete or incomplete information, while much is known for the case of finitely many actions, extensions to the case with infinite actions or with uncertainty are often considerably more difficult and some of them remain unsolved. Second, as a sort of reverse game theory, mechanism design aims to design particular games to achieve efficient outcomes or to maximize the revenues. A typical example is auction. To consider mechanism design in dynamic environments, novel tools beyond those used in the static problems need to be developed. Third, matching theory describes the formation of mutually beneficial relationships such as trading partnership, job placement and marriage. The evolution of such relationships over time plays an important role in various models and much remains to be explored.
