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Cooperation in Static and Dynamic Networks (talk recording available)
Dr. Siddharth Suri
Tuesday, September 30, 2014, 01:00pm - 02:00pm
Microsoft Research, New York City
This talk describes the results of a series of web-based, behavioral experiments designed to understand people's ability to cooperate in static and dynamic networks. In the context of static networks, it was previously thought that cooperation should fare better in highly clustered networks such as cliques than in networks with low clustering such as random networks. To test this hypothesis, we conducted a series of experiments, in which 24 individuals played a local public goods game arranged on one of five network topologies that varied between disconnected cliques and a random regular graph. In contrast with previous theoretical work, we found that network topology had no significant effect on average contributions. Since humans have a natural tendency to choose with whom to form new relationships and with whom to end established relationships, we also study cooperation in dynamic networks. Helping cooperators to mix assortatively is believed to reinforce the rewards accruing to mutual cooperation while simultaneously excluding defectors. Here we report on another series of human subjects experiments in which groups of 24 participants played a multi-player prisoner’s dilemma game where, critically, they were also allowed to propose and delete links to players of their own choosing at some variable rate. Over a wide variety of parameter settings and initial conditions, we found that endogenous partner selection significantly increased the level of cooperation, the average payoffs to players, and the assortativity between cooperators. Joint work with Jing Wang (NYU) and Duncan Watts (Microsoft Research).