Addressing issues of bounded rationality in economics has long been recognized as an important yet difficult problem. There has been a tremendous increase in research on complexity and bounded rationality in game theory due to the application of the notion of an automaton from computer science to problems in economics. This project can be divided into three areas: (1) continuing work on automation complexity but with a major focus on stochastic Bayesian games (repeated games with incomplete information); (2) applications of complexity analysis to economics; and (3) investigations of some new methods of bounding complexity in extensive games. The project will make important methodological contributions. The work on stochastic Bayesian games is important because it allows rigorous studies of decision making with differential private information. The research will contribute to our understanding of important and as yet unresolved issues such as the scope of equilibria attainable by bounded players, rule rationality versus full rationality, Bayesian updating by bounded players, and language and complexity. The project will apply strategic- complexity analysis to such important economic problems as market segmentation and the design of coordination of complex organizations using many bounded players.
