"In this proposal we aim to study the twin questions of a) how agents categorize decision problems (and in particular games) according to their similarity and b) how this categorization affects standard predictions in Game Theory. The most important contribution to the literature is that we endogenize the question of categorization, assuming that categorizations can be learned. Existing literature is characterized by making sometimes ad hoc assumptions on categorizations. Initial results have already shown that some of the key concepts used in Game Theory appear to be very fragile once the problem of categorization is introduced. We have also shown that many recent experimental results have a natural explanation in terms of learned categorizations. Possibly because of these results the research has already had quite some impact, reflected for example in a large number of seminar invitations. My personal background allows me to approach this issue in an interdisciplinary manner. Many cognitive scientists have been interested in the question of categorization and there are interesting applications even to Biology, in particular to the problem of genomic imprinting. Other applications in Economics concern bidding of firms in search or procurement auctions. Data from such applications can be used to test the theory. The project is executed at the Department of Economics at Maastricht University, in cooperation with an international group of top researchers working on closely related issues."