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Learning and Coordination in Networks

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In this talk I will discuss the results of several experiment we conducted to understand how people learn in network games and how this affects coordination and equilibrium selection in networks. We also study how network topology affects coordination and we show how this is connected to the participants’ learning. In particular we find that most participants can be characterized by (myopic) best response learning, but some participants are forward looking. Network topology interacts with learning by affecting the stability of best responses. This in turn affects how succesful coordination is and leads to a unique equilibrium selection in heterogenous networks.

This talk is part of the Microsoft Research Cambridge, public talks series.

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