AAAI Publications, Workshops at the Twenty-Fifth AAAI Conference on Artificial Intelligence

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Leadership Games and their Application in Super-Peer Networks
Thomas John Walsh, Javad Taheri, Jeremy Bryan Wright, Paul Cohen

Last modified: 2011-08-24


This paper considers a setting where a single ``leadership agent'' intervenes in a multi-agent system through actions that (perhaps subtly) change the dynamics of the system. We describe a number of forms this intervention can take and compare these situations to settings in previous work. We identify two important effects of leadership: faster system convergence, and convergence to a better equilibrium. Empirically, we first explore these properties in leadership of algorithms engaged in classical 2-player games. We then apply this general framework to the leadership of a super-peer file-sharing network. In these experiments the network contains some agents that make locally greedy decisions that hamper the network as a whole. We show that a leader acting based on a more global criteria can push the system to a better equilibrium point as well as speeding up convergence. We also show how a mathematical approximation of such super-peer networks can be used to aid a leader in determining a minimum-cost intervention strategy.

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