Makoto Yokoo received the B.E. and M.E. degrees in electrical engineering, in 1984 and 1986, respectively, form the University of Tokyo, Japan, and the Ph.D. degree in information and communication engineering in 1995, from the University of Tokyo, Japan. From 1986 to 2004, he was a research scientist of Nippon Telegraph and Telephone Corporation (NTT). He is currently a Professor of Information Science and Electrical Engineering, Kyushu University. His research interests include multi-agent systems, constraint satisfaction, and mechanism design among self-interested agents.
He served as a general co-chair of International Conference on Autonomous Agents and MultiAgent Systems in 2007 (AAMAS-2007), and as a program co-chair of AAMAS-2003. He is currently the president of International Foundation for Autonomous Agent and Multiagent Systems (IFAAMAS). He received the ACM SIGART Autonomous Agents Research Award in 2004, and the IFAAMAS influential paper award in 2010.
Repeated games provide a formal and quite general framework to examine why self-interested agents to cooperate in a long-term relationship. Formally, repeated games refer to a class of models where the same set of agents repeatedly play the same game, called the 'stage game', over a long (typically, infinite) time horizon. The case where agents can perfectly observe each other's actions (perfect monitoring) is extensively studied; there exist rich theoretical results including the well-known folk theorem, which shows that any cooperative outcome is possible under several mild assumptions. However, in reality, long term relationships are often plagued by imperfect monitoring, i.e., agents cannot directly observe each other's actions; they observe signals that imperfectly reveal what actions have been taken. Repeated games with imperfect monitoring are classified into two categories: the case of public monitoring, where players commonly observe a public signal, and the case of private monitoring. where each player observes a signal that is not observable to others. The imperfect public monitoring case shares many features with the perfect monitoring case, and we now have a good understanding of how it works. In contrast, the imperfect private monitoring case is still in its infancy. However, quite recently, we found that there exists a strong relationship between the equilibrium analysis in the imperfect private monitoring case and POMDP planning. In this talk, I sketch the main results of repeated games and describe how we can utilize POMDP techniques to analyze an equilibrium in the imperfect private monitoring case.