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Dynamic Coordination in Large Networks

(gefördert von der DFG im Rahmen der Exzellenzinitiative, 2012 - 2016)

Our focus is the analysis of dynamics in large networked systems such as traffic systems, wireless networks, the Internet, or social networks. In these systems, central coordination of user behavior is often impossible. Instead, distributed and decentralized protocols are needed in order to obtain efficient solutions for coordination problems. Our aim is the analysis and characterization of these systems and the design of efficient algorithms - for instance, distributed learning algorithms for throughput maximization in wireless networks, or routing protocols for rational and selfish users in traffic networks. A special focus are game-theoretic approaches that model rational behavior of individual users in the system and set appropriate incentives that lead the system into globally efficient states. In addition, we analyze natural dynamics and their convergence properties in social networks.