Abstract

In this paper we study a large class of non-atomic games arising from interactions on the Internet, such as many users sharing a network link, researchers accessing a database or web server, subscribers to a network services provider trying to gain access to the modem pool and many more. We provide simple and easily computable conditions under which these games are learnable by several models of learning, such as adaptive and sophisticated learning (Milgrom and Roberts [34]), calibrated learning (Foster and Vohra [8]), and reasonable learning (Friedman and Shenker [15]). Thus, using these methods one can evaluate the stability of such games on the Internet or in other settings in which players must learn over time. Running head: Learnability in Internet Games I would like to thank Michelle Goman, Adam Landsberg, Herv'e Moulin, and Scott Shenker for helpful conversations. An earlier version of this paper was circulated under the title "Non-Atomic Games with Multiple Externali...

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